Search results for: social research networks sites (SRNS)

Authors: L. Parisi

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Kinematic data wisely correlate vector quantities in space to scalar parameters in time to assess the degree of symmetry between the intact limb and the amputated limb with respect to a normal model derived from the gait of control group participants. Furthermore, these particular data allow a doctor to preliminarily evaluate the usefulness of a certain rehabilitation therapy. Kinetic curves allow the analysis of ground reaction forces (GRFs) to assess the appropriateness of human motion. Electromyography (EMG) allows the analysis of the fundamental lower limb force contributions to quantify the level of gait asymmetry. However, the use of this technological tool is expensive and requires patient’s hospitalization. This research work suggests overcoming the above limitations by applying artificial neural networks.

Keywords: kinetics, kinematics, cyclograms, neural networks, transtibial amputation

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Authors: Daniel Gredig, Annabelle Bartelsen-Raemy

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Social work professionals should underpin their decisions with scientific knowledge and research findings. Hence, research is used as a framework for social work education and research courses have become a taken-for-granted component of study programmes. However, it has been acknowledged that social work students have negative beliefs and attitudes as well as frequently feelings of fear of research courses. Against this background, the present study aimed to establish the relationship between student’s fear of research courses, their research orientation and interest in research courses. We hypothesized that fear predicts the interest in research courses. Further, we hypothesized that research orientation (perceived importance and attributed usefulness for research for social work practice and perceived unbiased nature of research) was a mediating variable. In the years 2014, 2015 and 2016, we invited students enrolled for a bachelor programme in social work in Switzerland to participate in the study during their introduction day to the school taking place two weeks before their programme started. For data collection, we used an anonymous self-administered on-line questionnaire filled in on site. Data were analysed using descriptive statistics and structural equation modelling (generalized least squares estimates method). The sample included 708 students enrolled in a social work bachelor-programme, 501 being female, 184 male, and 5 intersexual, aged 19–56, having various entitlements to study, and registered for three different types of programme modes (full time programme; part time study with field placements in blocks; part time study involving concurrent field placement). Analysis showed that the interest in research courses was predicted by fear of research courses (β = -0.29) as well as by the perceived importance (β = 0.27), attributed usefulness of research (β = 0.15) and perceived unbiased nature of research (β = 0.08). These variables were predicted, in turn, by fear of research courses (β = -0.10, β = -0.23, and β = -0.13). Moreover, interest was predicted by age (β = 0.13). Fear of research courses was predicted by age (β = -0.10) female gender (β = 0.28) and having completed a general baccalaureate (β = -0.09). (GFI = 0.997, AGFI = 0.988, SRMR = 0.016, CMIN/df = 0.946, adj. R2 = 0.312). Findings evidence a direct as well as a mediated impact of fear on the interest in research courses in entering first-year students in a social work bachelor-programme. It highlights one of the challenges social work education in a research framework has to meet with. It seems, there have been considerable efforts to address the research orientation of students. However, these findings point out that, additionally, research anxiety in terms of fear of research courses should be considered and addressed by teachers when conceptualizing research courses.

Keywords: research anxiety, research courses, research interest, research orientation, social work students, teaching

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Authors: Pau Rodriguez, Jordi Gonzalez, Josep M. Gonfaus, Xavier Roca

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Image sharing in social networks has increased exponentially in the past years. Officially, there are 600 million Instagrammers uploading around 100 million photos and videos per day. Consequently, there is a need for developing new tools to understand the content expressed in shared images, which will greatly benefit social media communication and will enable broad and promising applications in education, advertisement, entertainment, and also psychology. Following these trends, our work aims to take advantage of the existing relationship between text and personality, already demonstrated by multiple researchers, so that we can prove that there exists a relationship between images and personality as well. To achieve this goal, we consider that images posted on social networks are typically conditioned on specific words, or hashtags, therefore any relationship between text and personality can also be observed with those posted images. Our proposal makes use of the most recent image understanding models based on neural networks to process the vast amount of data generated by social users to determine those images most correlated with personality traits. The final aim is to train a weakly-supervised image-based model for personality assessment that can be used even when textual data is not available, which is an increasing trend. The procedure is described next: we explore the images directly publicly shared by users based on those accompanying texts or hashtags most strongly related to personality traits as described by the OCEAN model. These images will be used for personality prediction since they have the potential to convey more complex ideas, concepts, and emotions. As a result, the use of images in personality questionnaires will provide a deeper understanding of respondents than through words alone. In other words, from the images posted with specific tags, we train a deep learning model based on neural networks, that learns to extract a personality representation from a picture and use it to automatically find the personality that best explains such a picture. Subsequently, a deep neural network model is learned from thousands of images associated with hashtags correlated to OCEAN traits. We then analyze the network activations to identify those pictures that maximally activate the neurons: the most characteristic visual features per personality trait will thus emerge since the filters of the convolutional layers of the neural model are learned to be optimally activated depending on each personality trait. For example, among the pictures that maximally activate the high Openness trait, we can see pictures of books, the moon, and the sky. For high Conscientiousness, most of the images are photographs of food, especially healthy food. The high Extraversion output is mostly activated by pictures of a lot of people. In high Agreeableness images, we mostly see flower pictures. Lastly, in the Neuroticism trait, we observe that the high score is maximally activated by animal pets like cats or dogs. In summary, despite the huge intra-class and inter-class variabilities of the images associated to each OCEAN traits, we found that there are consistencies between visual patterns of those images whose hashtags are most correlated to each trait.

Keywords: emotions and effects of mood, social impact theory in social psychology, social influence, social structure and social networks

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Authors: Driss Bouyahya

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During the late 1960s, Islam-oriented social movements have encroached to reach the Moroccan public spheres and mobilize huge waves of people from different walks of life under the banners of a rhetoric that resonates with the Muslim way of life away from Modernity and globalization tenets. In this respect, the present study investigates and explores some of the ways utilized by the Movement for Unity and Reform in Morocco as an Islam-oriented movement to recruit students massively at universities. The significance of this study lies in demystifying the recruitment strategies and mechanisms, considered essential for the Islam-oriented social movements to mobilize. This research paper uses a quantitative method to collect and analyze data through two different structured questionnaires. One of the major findings is that this Islam-oriented movement uses different techniques to recruit students, namely social networks, its websites and You-tube as three main modern and sophisticated means of communication. In a nutshell, this paper´s findings fill some of the gaps in the literature in regard to Islam-oriented movements ‘mobilization strategies.

Keywords: changing, ideology, Islam, party

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Authors: Xuhui Lin, Qiuchen Lu, Yi An, Tao Yang

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As global climate change intensifies, extreme weather events such as floods increasingly threaten urban infrastructure, making the vulnerability of urban road networks a pressing issue. Existing static repair strategies fail to adapt to the rapid changes in road network conditions during flood events, leading to inefficient resource allocation and suboptimal recovery. The main research gap lies in the lack of repair strategies that consider both the dynamic characteristics of networks and the progression of flood propagation. This paper proposes a topology-based dynamic repair strategy that adjusts repair priorities based on real-time changes in flood propagation and traffic demand. Specifically, a novel method is developed to assess and enhance the resilience of urban road networks during flood events. The method combines road network topological analysis, flood propagation modelling, and traffic flow simulation, introducing a local importance metric to dynamically evaluate the significance of road segments across different spatial and temporal scales. Using London's road network and rainfall data as a case study, the effectiveness of this dynamic strategy is compared to traditional and Transport for London (TFL) strategies. The most significant highlight of the research is that the dynamic strategy substantially reduced the number of stranded vehicles across different traffic demand periods, improving efficiency by up to 35.2%. The advantage of this method lies in its ability to adapt in real-time to changes in network conditions, enabling more precise resource allocation and more efficient repair processes. This dynamic strategy offers significant value to urban planners, traffic management departments, and emergency response teams, helping them better respond to extreme weather events like floods, enhance overall urban resilience, and reduce economic losses and social impacts.

Keywords: Urban resilience, road networks, flood response, dynamic repair strategy, topological analysis

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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Authors: Naim Karasekreter, Ugur Fidan, Fatih Basciftci

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Wireless sensor networks are networks in which more than one sensor node is organized among themselves. The working principle is based on the transfer of the sensed data over the other nodes in the network to the central station. Wireless sensor networks concentrate on routing algorithms, energy efficiency and clustering algorithms. In the clustering method, the nodes in the network are divided into clusters using different parameters and the most suitable cluster head is selected from among them. The data to be sent to the center is sent per cluster, and the cluster head is transmitted to the center. With this method, the network traffic is reduced and the energy efficiency of the nodes is increased. In this study, clustering algorithms were examined in terms of clustering performances and cluster head selection characteristics to try to identify weak and strong sides. This work is supported by the Project 17.Kariyer.123 of Afyon Kocatepe University BAP Commission.

Keywords: wireless sensor networks (WSN), clustering algorithm, cluster head, clustering

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Authors: Hamad Almebayedh, Chuxia Lin, Yu wang

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The environmental impact assessment (EIA) must be improved, assessed, and quality checked for human and environmental health and safety. Soil contamination is expanding, and sites and soil remediation activities proceeding around the word which simplifies the answer “quality soil characterization” will lead to “quality EIA” to illuminate the contamination level and extent and reveal the unknown for the way forward to remediate, countifying, containing, minimizing and eliminating the environmental damage. Spatial interpolation methods play a significant role in decision making, planning remediation strategies, environmental management, and risk assessment, as it provides essential elements towards site characterization, which need to be informed into the EIA. The Innovative 3D soil mapping and soil characterization technology presented in this research paper reveal the unknown information and the extent of the contaminated soil in specific and enhance soil characterization information in general which will be reflected in improving the information provided in developing the EIA related to specific sites. The foremost aims of this research paper are to present novel 3D mapping technology to quality and cost-effectively characterize and estimate the distribution of key soil characteristics in contaminated sites and develop Innovative process/procedure “assessment measures” for EIA quality and assessment. The contaminated site and field investigation was conducted by innovative 3D mapping technology to characterize the composition of petroleum hydrocarbons contaminated soils in a decommissioned oilfield waste pit in Kuwait. The results show the depth and extent of the contamination, which has been interred into a developed assessment process and procedure for the EIA quality review checklist to enhance the EIA and drive remediation and risk assessment strategies. We have concluded that to minimize the possible adverse environmental impacts on the investigated site in Kuwait, the soil-capping approach may be sufficient and may represent a cost-effective management option as the environmental risk from the contaminated soils is considered to be relatively low. This research paper adopts a multi-method approach involving reviewing the existing literature related to the research area, case studies, and computer simulation.

Keywords: quality EIA, spatial interpolation, soil characterization, contaminated site

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Authors: Ashima Anurag Sharma

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Optical fiber based networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This research paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparison between various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

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Authors: Qingqing Zhao, Junhong Bai

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To investigate the effects of salinity on dynamics of soil carbon and nitrogen contents and stocks, soil samples were collected at a depth of 30 cm at four sampling sites (Sites B, T, S and P) along a salinity gradient in a drained coastal wetland, the Yellow River Delta, China. The salinity of these four sites ranked in the order: B (8.68±4.25 ms/cm) > T (5.89±3.17 ms/cm) > S (3.19±1.01 ms/cm) > P (2.26±0.39 ms/cm). Soil total carbon (TC), soil organic carbon (SOC), soil microbial biomass carbon (MBC), soil total nitrogen (TC) and soil microbial biomass carbon (MBC) were measured. Based on these data, soil organic carbon density (SOCD), soil microbial biomass carbon density (MBCD), soil nitrogen density (TCD) and soil microbial biomass nitrogen density (MBND) were calculated at four sites. The results showed that the mean concentrations of TC, SOC, MBC, TN and MBN showed a general deceasing tendency with increasing salinities in the top 30 cm of soils. The values of SOCD, MBCD, TND and MBND exhibited similar tendency along the salinity gradient. As for profile distribution pattern, The C/N ratios ranged from 8.28 to 56. 51. Higher C/N ratios were found in samples with high salinity. Correlation analysis showed that the concentrations of TC, SOC and MBC at four sampling sites were significantly negatively correlated with salinity (P < 0.01 or P < 0.05), indicating that salinity could inhibit soil carbon accumulation. However, no significant relationship was observed between TN, MBN and salinity (P > 0.05).

Keywords: carbon content and stock, nitrogen content and stock, salinity, coastal wetland

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Authors: M. Hadjisoteriou, A. Kyriacou Petrou

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This paper will discuss ideas of social sustainability in urban design and human behavior in multicultural contested sites. It will focus on the potential of the re-reading of the “site” through mapping that acts as a research methodology and will discuss the chosen site of Mouttalos, Cyprus as a place of multiple identities. Through a methodology of mapping using a bottom up approach, a process of disassembling derives that acts as a mechanism to re-examine space and place by searching for the invisible and the non-measurable, understanding the site through its detailed inhabitation patterns. The significance of this study lies in the use of mapping as an active form of thinking rather than a passive process of representation that allows for a new site to be discovered, giving multiple opportunities for adaptive urban strategies and socially engaged design approaches. We will discuss the above thematic based on the chosen contested site of Mouttalos, a small Turkish Cypriot neighbourhood, in the old centre of Paphos (Ktima), SW of Cyprus. During the political unrest, between Greek and Turkish Cypriot communities, in 1963, the area became an enclave to the Turkish Cypriots, excluding any contact with the rest of the area. Following the Turkish invasion of 1974, the residents left their homes, plots and workplaces, resettling in the North of Cyprus. Greek Cypriot refugees moved into the area. The presence of the Greek Cypriot refugees is still considered to be a temporary resettlement. The buildings and the residents themselves exist in a state of uncertainty. The site is documented through a series of parallel investigations into the physical conditions and history of the site. Research methodologies use the process of mapping to expose the complex and often invisible layers of information that coexist. By registering the site through the subjective experiences, and everyday stories of inhabitants, a series of cartographic recordings reveals the space between: happening and narrative and especially space between different cultures and religions. Research put specific emphasis on engaging the public, promoting social interaction, identifying spatial patterns of occupation by previous inhabitants through social media. Findings exposed three main areas of interest. Firstly we identified inter-dependent relationships between permanence and temporality, characterised by elements such us, signage through layers of time, past events and periodical street festivals, unfolding memory and belonging. Secondly issues of co-ownership and occupation, found through particular narratives of exchange between the two communities and through appropriation of space. Finally formal and informal inhabitation of space, revealed through the presence of informal shared back yards, alternative paths, porous street edges and formal and informal landmarks. The importance of the above findings, was achieving a shift of focus from the built infrastructure to the soft network of multiple and complex relations of dependence and autonomy. Proposed interventions for this contested site were informed and led by a new multicultural identity where invisible qualities were revealed though the process of mapping, taking on issues of layers of time, formal and informal inhabitation and the “permanence of the temporary”.

Keywords: contested sites, mapping, social sustainability, temporary urban strategies

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Authors: Havva Nur Tarakci, Bahar Urhan Torun

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The transformation that is seen in every area of life by technology, especially internet technology changes the structure of political communications too. Internet, which is at the top of new communication technologies, affects political communications with its structure in a way that no traditional communication tools ever have and enables interaction and the channel between receiver and sender, and it becomes one of the most effective tools preferred among the political communication applications. This state as a result of technological convergence makes Internet an unobtainable place for political communication campaigns. Political communications, which means every kind of communication strategies that political parties called 'actors of political communications' use with the aim of messaging their opinions and party programmes to their present and potential voters who are a target group for them, is a type of communication that is frequently used also among social media tools at the present day. The electorate consisting of different structures is informed, directed, and managed by social media tools. Political parties easily reach their electorate by these tools without any limitations of both time and place and also are able to take the opinions and reactions of their electorate by the element of interaction that is a feature of social media. In this context, Facebook, which is a place that political parties use in social media at most, is a communication network including in our daily life since 2004. As it is one of the most popular social networks today, it is among the most-visited websites in the global scale. In this way, the research is based on the question, “How do the political parties use Facebook at the campaigns, which they conduct during the election periods, for informing their voters?” and it aims at clarifying the Facebook using practices of the political parties. In direction of this objective the official Facebook accounts of the four political parties (JDP–AKParti, PDP–BDP, RPP-CHP, NMP-MHP), which reach their voters by social media besides other communication tools, are treated, and a frame for the politics of Turkey is formed. The time of examination is constricted with totally two weeks, one week before the mayoral elections and one week after the mayoral elections, when it is supposed that the political parties use their Facebook accounts in full swing. As a research method, the method of content analysis is preferred, and the texts and the visual elements that are gotten are interpreted based on this analysis.

Keywords: Facebook, political communications, social media, electrorate

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Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

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Authors: Jaime E. Fernandez, Pablo J. Valverde

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This paper presents a methodological approach that aims to contrast/validate theoretical results from a corruption network game through probabilistic analysis of simulated microdata using Bayesian Networks (BNs). The research develops a public corruption model in a game theory framework. Theoretical results suggest a series of 'optimal settings' of model's exogenous parameters that boost the emergence of corruption. The paper contrasts these outcomes with probabilistic inference results based on BNs adjusted over simulated microdata. Principal findings indicate that probabilistic reasoning based on BNs significantly improves parameter specification and causal analysis in a public corruption game.

Keywords: Bayesian networks, probabilistic reasoning, public corruption, theoretical games

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Authors: Shadrack Mambo, Karim Djouani, Yskandar Hamam, Barend van Wyk, Patrick Siarry

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This paper discusses the current trends in medical image registration techniques and addresses the need to provide a solid theoretical foundation for research endeavours. Methodological analysis and synthesis of quality literature was done, providing a platform for developing a good foundation for research study in this field which is crucial in understanding the existing levels of knowledge. Research on medical image registration techniques assists clinical and medical practitioners in diagnosis of tumours and lesion in anatomical organs, thereby enhancing fast and accurate curative treatment of patients. Literature review aims to provide a solid theoretical foundation for research endeavours in image registration techniques. Developing a solid foundation for a research study is possible through a methodological analysis and synthesis of existing contributions. Out of these considerations, the aim of this paper is to enhance the scientific community’s understanding of the current status of research in medical image registration techniques and also communicate to them, the contribution of this research in the field of image processing. The gaps identified in current techniques can be closed by use of artificial neural networks that form learning systems designed to minimise error function. The paper also suggests several areas of future research in the image registration.

Keywords: image registration techniques, medical images, neural networks, optimisaztion, transformation

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Authors: Majdah Alnefaie

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The ‘netnographic study’ and data mining have been used to monitor the public interaction on Social Media Sites (SMSs) to understand what the motivational factors influence the Saudi intentions regarding allowing women driving in Saudi Arabia in 2018. The netnographic study monitored the publics’ textual and visual communications in Twitter, Snapchat, and YouTube. SMSs users’ communications method is also known as electronic word of mouth (eWOM). Netnography methodology is still in its initial stages as it depends on manual extraction, reading and classification of SMSs users text. On the other hand, data mining is come from the computer and physical sciences background, therefore it is much harder to extract meaning from unstructured qualitative data. In addition, the new development in data mining software does not support the Arabic text, especially local slang in Saudi Arabia. Therefore, collaborations between social and computer scientists such as ‘netnographic study’ and data mining will enhance the efficiency of this study methodology leading to comprehensive research outcome. The eWOM communications between individuals on SMSs can promote a sense that sharing their preferences and experiences regarding politics and social government regulations is a part of their daily life, highlighting the importance of using SMSs as assistance in promoting participation in political and social. Therefore, public interactions on SMSs are important tools to comprehend people’s intentions regarding the new government regulations in the country. This study aims to answer this question, "What factors influence the Saudi Arabians' intentions of Saudi female's car-driving in 2018". The study utilized qualitative method known as netnographic study. The study used R studio to collect and analyses 27000 Saudi users’ comments from 25th May until 25th June 2018. The study has developed data collection model that support importing and analysing the Arabic text in the local slang. The data collection model in this study has been clustered based on different type of social networks, gender and the study main factors. The social network analysis was employed to collect comments from SMSs owned by governments’ originations, celebrities, vloggers, social activist and news SMSs accounts. The comments were collected from both males and females SMSs users. The sentiment analysis shows that the total number of positive comments Saudi females car driving was higher than negative comments. The data have provided the most important factors influenced the Saudi Arabians’ intention of Saudi females car driving including, culture and environment, freedom of choice, equal opportunities, security and safety. The most interesting finding indicted that women driving would play a role in increasing the individual freedom of choice. Saudi female will be able to drive cars to fulfill her daily life and family needs without being stressed due to the lack of transportation. The study outcome will help Saudi government to improve woman quality of life by increasing the ability to find more jobs and studies, increasing income through decreasing the spending on transport means such as taxi and having more freedom of choice in woman daily life needs. The study enhances the importance of using use marketing research to measure the public opinions on the new government regulations in the country. The study has explained the limitations and suggestions for future research.

Keywords: netnographic study, data mining, social media, Saudi Arabia, female driving

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Authors: Auliya Adzilatin Uzhma, Ismu Rini Dwi, I. Nyoman Suluh Wijaya

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Corporate Social Responsibility (CSR) programme in Pantai Harapan Jaya village is cultivation of mangrove and fishery capital distribution, to achieve the goal the CSR programme needed participation from the society in it. Moeliono in Fahrudin (2011) mentioned that participation from society is based by intrinsic reason from inside people it self and extrinsic reason from the other who related to him. The fundamental connection who caused more boundaries from action which the organization can do called the social structure. The purpose of this research is to know the form of public participation and the social structure typology of the villager and people who is participated in CSR programme. The key actors of the society and key actors of the people who’s participated also can be known. This research use Social Network Analysis method by knew the Rate of Participation, Density and Centrality. The result of the research is people who is involved in the programme is lived in Dusun Pondok Dua and they work in fisheries field. The density value from the participant is 0.516 it’s mean that 51.6% of the people that participated is involved in the same step of CSR programme.

Keywords: social structure, social network analysis, corporate social responsibility, public participation

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Authors: Cetin Arslan, Senol Tayan

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Social media is one of the most important and effective means of social interaction among people in which they create, share and exchange their ideas via photos, videos or voice messages. Although there are lots of communication tools, social media sites are the most prominent ones that allows the users articulate themselves in a matter of seconds all around the world with almost any expenses and thus, they became very popular and widespread after its emergence. As the usage of social media increases, it becomes an effective instrument in social matters. While it is possible to use social media to emphasize basic human rights and protest some failures of any government as in “Arab Spring”, it is also possible to spread propaganda and misinformation just to cause long lasting insurgency, upheaval, turmoil or disorder as an instrument of intervention to internal affairs and state sovereignty by some hostile groups or countries. It is certain that “social media” has positive effects on democracies letting people have chance to express themselves and to organize, but it is also obvious that the misuse of it, is very common that even a five-minute-long video can cause to wage a campaign against a country. Although it looks anti-democratic, when you consider the catastrophic effects of misuse of social media, it is a kind of area that serious precautions are to be taken without limiting democratic rights while allowing constant and perpetual share but preventing the criminal events. This article begins with the current developments in social media and gives some examples on misuse of it. Second part tries to put emphasize on the legal basis that can prevent criminal activities and the upheavals and insurgencies against state security. Last part makes comparison between democratic countries and international organizations’’ actions against such activities and proposes some further actions that are compatible with democratic norms.

Keywords: democracy, disorder, security, Social Media

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Authors: Redouane Tlemsani, Redouane, Belkacem Kouninef, Abdelkader Benyettou

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In this paper, our system is a Markovien system which we can see it like a Dynamic Bayesian Networks. One of the major interests of these systems resides in the complete training of the models (topology and parameters) starting from training data. The Bayesian Networks are representing models of dubious knowledge on complex phenomena. They are a union between the theory of probability and the graph theory in order to give effective tools to represent a joined probability distribution on a set of random variables. The representation of knowledge bases on description, by graphs, relations of causality existing between the variables defining the field of study. The theory of Dynamic Bayesian Networks is a generalization of the Bayesians networks to the dynamic processes. Our objective amounts finding the better structure which represents the relationships (dependencies) between the variables of a dynamic bayesian network. In applications in pattern recognition, one will carry out the fixing of the structure which obliges us to admit some strong assumptions (for example independence between some variables).

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, networks

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Authors: Victor Radich, Tania Basso, Regina Moraes

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Lead qualification is one of the main procedures in Customer Relationship Management (CRM) projects. Its main goal is to identify potential consumers who have the ideal characteristics to establish a profitable and long-term relationship with a certain organization. Social networks can be an important source of data for identifying and qualifying leads since interest in specific products or services can be identified from the users’ expressed feelings of (dis)satisfaction. In this context, this work proposes the use of machine learning techniques and sentiment analysis as an extra step in the lead qualification process in order to improve it. In addition to machine learning models, sentiment analysis or opinion mining can be used to understand the evaluation that the user makes of a particular service, product, or brand. The results obtained so far have shown that it is possible to extract data from social networks and combine the techniques for a more complete classification.

Keywords: lead qualification, sentiment analysis, opinion mining, machine learning, CRM, lead scoring

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Authors: R. Sudhesh Solomon, P. Y. K. L. Srinivas, Abhay Narayan, Amitava Das

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Users in social networks either unicast or broadcast their messages. At mention is the popular way of unicasting for Twitter whereas general tweeting could be considered as broadcasting method. Understanding the information flow and dynamics within a Social Network and modeling the same is a promising and an open research area called Information Diffusion. This paper seeks an answer to a fundamental question - understanding if the at-mention network or the unicasting pattern in social media is purely random in nature or is there any user specific selectional preference? To answer the question we present an empirical analysis to understand the sociological aspects of Twitter mentions network within a social network community. To understand the sociological behavior we analyze the values (Schwartz model: Achievement, Benevolence, Conformity, Hedonism, Power, Security, Self-Direction, Stimulation, Traditional and Universalism) of all the users. Empirical results suggest that values traits are indeed salient cue to understand how the mention-based communication network functions. For example, we notice that individuals possessing similar values unicast among themselves more often than with other value type people. We also observe that traditional and self-directed people do not maintain very close relationship in the network with the people of different values traits.

Keywords: information diffusion, personality and values, social network analysis, twitter mentions network

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Authors: Mohsen Azarmjoo, Mehdi Mehdizadeh Koupaei, Maryam Mehdizadeh Koupaei, Asghar Mahdlouei Azar

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The increasing prevalence of wireless networks in our daily lives has made them indispensable. The aim of this research is to investigate the management of information transfer in wireless networks and the integration of renewable solar energy resources in a residential building. The focus is on the transmission of electricity and information through wireless networks, as well as the utilization of sensors and wireless fire alarm systems. The research employs a descriptive approach to examine the transmission of electricity and information on a wireless network with electric and optical telephone lines. It also investigates the transmission of signals from sensors and wireless fire alarm systems via radio waves. The methodology includes a detailed analysis of security, comfort conditions, and costs related to the utilization of wireless networks and renewable solar energy resources. The study reveals that it is feasible to transmit electricity on a network cable using two pairs of network cables without the need for separate power cabling. Additionally, the integration of renewable solar energy systems in residential buildings can reduce dependence on traditional energy carriers. The use of sensors and wireless remote information processing can enhance the safety and efficiency of energy usage in buildings and the surrounding spaces.

Keywords: renewable energy, intelligentization, wireless sensors, fire alarm system

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Authors: Priya Sepaha

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Social media has loomed as the most effective tool in recent times to flag the causes, contents, opinions and direction of any social movement and has demonstrated that it will have a far-reaching effect on government as well. This study focuses on India which has emerged as the fastest growing community on social media. Social movement activists, in particular, have extensively utilized the power of digital social media to streamline the effectiveness of social protest on a particular issue through extensive successful mass mobilizations. This research analyses the role and impact of social media as a power to catalyze the social movements in India and further seeks to describe how certain social movements are resisted, subverted, co-opted and/or deployed by social media. The impact assessment study has been made with the help of cases, policies and some social movement which India has witnessed the assertion of numerous social issues perturbing the public which eventually paved the way for remarkable judicial decisions. The paper concludes with the observations that despite its pros and cons, the impacts of social media on the functioning of the Indian Government have demonstrated that it has already become an indispensable tool in the hands of social media-suave Indians who are committed to bring about a desired change.

Keywords: social media, social movements, impact, law, government

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Authors: Nabil Elkhatri, Mohamed Louay Metougui, Ngonidzashe Chirinda

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Mining activities have left a legacy of degraded landscapes, prompting urgent efforts for ecological restoration. Reforestation holds promise as a potent tool to rehabilitate these old mining sites, with the potential to sequester carbon and contribute to climate change mitigation. This study focuses on evaluating the carbon stock and sequestration potential of reforestation species in the context of Morocco's mining areas, employing the DeNitrification-DeComposition (DNDC) model. The research is grounded in recognizing the need to connect theoretical models with practical implementation, ensuring that reforestation efforts are informed by accurate and context-specific data. Field data collection encompasses growth patterns, biomass accumulation, and carbon sequestration rates, establishing an empirical foundation for the study's analyses. By integrating the collected data with the DNDC model, the study aims to provide a comprehensive understanding of carbon dynamics within reforested ecosystems on old mining sites. The major findings reveal varying sequestration rates among different reforestation species, indicating the potential for species-specific optimization of reforestation strategies to enhance carbon capture. This research's significance lies in its potential to contribute to sustainable land management practices and climate change mitigation strategies. By quantifying the carbon stock and sequestration potential of reforestation species, the study serves as a valuable resource for policymakers, land managers, and practitioners involved in ecological restoration and carbon management. Ultimately, the study aligns with global objectives to rejuvenate degraded landscapes while addressing pressing climate challenges.

Keywords: carbon stock, carbon sequestration, DNDC model, ecological restoration, mining sites, Morocco, reforestation, sustainable land management.

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Authors: Ekapon Thienthaworn

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This research aims to study the reliability of the forecasting factor in social media by using survey research methods with questionnaires. The sampling is the group of undergraduate students in Bangkok. A multiple-step random number of 400 persons, data analysis are descriptive statistics with multivariate regression analysis. The research found the average of the overall trust at the intermediate level for reading the news in social media and the results of the multivariate regression analysis to find out the factors that forecast credibility of the media found the only content that has the power to forecast reliability of undergraduate students in Bangkok to reading the news on social media at the significance level.at 0.05.These can be factors with forecasts reliability of news in social media by a variable that has the highest influence factor of the media content and the speed is also important for reliability of the news.

Keywords: credibility of news, behaviors and attitudes, social media, web board

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Authors: Oluwatosin Olofintoye, Josiah Adeyemo, Gbemileke Shomade

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The relationship between rainfall and runoff is an important issue in surface water hydrology therefore the understanding and development of accurate rainfall-runoff models and their applications in water resources planning, management and operation are of paramount importance in hydrological studies. This paper reviews some of the previous works on the rainfall-runoff process modeling. The hydrologic applications of conceptual models and artificial neural networks (ANNs) for the precipitation-runoff process modeling were studied. Gradient training methods such as error back-propagation (BP) and evolutionary algorithms (EAs) are discussed in relation to the training of artificial neural networks and it is shown that application of EAs to artificial neural networks training could be an alternative to other training methods. Therefore, further research interest to exploit the abundant expert knowledge in the area of artificial intelligence for the solution of hydrologic and water resources planning and management problems is needed.

Keywords: artificial intelligence, artificial neural networks, evolutionary algorithms, gradient training method, rainfall-runoff model

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Authors: Joyce Mary Adam

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The subject of youth and education has been on the agenda of both public policies and specific education policies. In this sense, this work aims to discuss, based on the conceptions of social capital and cultural capital, the possibilities of elaborating and putting into practice the life projects they build during secondary school. The critical view brought by the concepts of social capital and cultural capital considers that in the school environment, those who have social capital and cultural capital have more tools to continue their projects, while those who do not have such capital will consequently have fewer opportunities, a fact that directly contributes to the perpetuation of social and educational inequality. When the "Life Project" is discussed under the sole responsibility of the students, it is clear that it is the students who must "take their responsibilities and decisions", their success or failure. From this point of view, the success of the implementation of the Life Project is determined by how well the students have developed their "skills and competencies" and their capacity for entrepreneurship without promoting a critical reflection on the real economic difficulties of the majority of students at this level of education. This situation gives rise to feelings of self-blame and self-responsibility among young people, who are compelled to confront the reality that their expectations have not been fulfilled, that they have been unable to gain employment, and, in some instances, that they have been marginalized. In this regard, the research project aimed to gather data on the living conditions of students at a public school and a private school in Brazil through interviews. The research methodology was interviews with students from a public school and an elite private school. The main objective of the research was to analyze the students' cultural and social capital as a key element in their social and professional integration after completing this stage of education. The study showed that social and cultural capital has a significant influence on opportunities to continue studying or to find a satisfactory job. For young people from public schools and from lower economic classes, the need to enter the job market as soon as they finish or even before they finish high school is due to economic and survival issues. The hours of dedication to studies and the diversity of cultural activities such as trips, visits to museums, or the cultivation of artistic activities available to poorer students in state schools have proved to be rarer. In conclusion, we found that the difference in social and cultural capital between the young people taking part in the research has been shown to play an important role in the social and professional integration of the students and contributes to the maintenance of school and social inequality. This highlights the importance of public policies and support networks for young people leaving secondary school.

Keywords: social capital, cultural capital, high school, life project, social insertion, professional insertion, youth

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Authors: Carly Madge, Melanie Zurba, Ryan Bullock

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The Boreal Forest has experienced some of the most drastic climate change-induced temperature rises in Canada, with average winter temperatures increasing by 3°C since 1948. One of the main concerns of the province of Saskatchewan, and particularly wildfire managers, is the increased risk of wildfires due to climate change. With these concerns in mind Sakaw Askiy Management Inc., a forestry corporation located in Prince Albert, Saskatchewan with operations in the Boreal Forest biome, is developing wildfire risk reduction strategies that are supported by the shareholders of the corporation as well as the stakeholders of the Prince Albert Forest Management Area (which includes citizens, hunters, trappers, cottage owners, and outfitters). In the past, wildfire management strategies implemented through harvesting have been received with skepticism by some community members of Prince Albert. Engagement of the stakeholders of the Prince Albert Management Area through the development of the wildfire risk reduction strategies aims to reduce this skepticism and rebuild some of the trust that has been lost between industry and community. This research project works with the framework of social learning, which is defined as the learning that occurs when individuals come together to form a group with the purpose of understanding environmental challenges and determining appropriate responses to them. The project evaluates the social learning processes that occur through the development of the risk reduction strategies and how the learning has allowed Sakaw to work towards implementing the strategies into their forest harvesting plans. The incorporation of wildfire risk reduction strategies works to increase the adaptive capacity of Sakaw, which in this case refers to the ability to adjust to climate change, moderate potential damages, take advantage of opportunities, and cope with consequences. Using semi-structured interviews and wildfire workshop meetings shareholders and stakeholders shared their knowledge of wildfire, their main wildfire concerns, and changes they would like to see made in the Prince Albert Forest Management Area. Interviews and topics discussed in the workshops were inductively coded for themes related to learning, adaptive capacity, areas of concern, and preferred methods of wildfire risk reduction strategies. Analysis determined that some of the learning that has occurred has resulted through social interactions and the development of networks oriented towards wildfire and wildfire risk reduction strategies. Participants have learned new knowledge and skills regarding wildfire risk reduction. The formation of wildfire networks increases access to information on wildfire and the social capital (trust and strengthened relations) of wildfire personnel. Both factors can be attributed to increases in adaptive capacity. Interview results were shared with the General Manager of Sakaw, where the areas of concern and preferred strategies of wildfire risk reduction will be considered and accounted for in the implementation of new harvesting plans. This research also augments the growing conceptual and empirical evidence of the important role of learning and networks in regional wildfire risk management efforts.

Keywords: adaptive capacity, community-engagement, social learning, wildfire risk reduction

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Authors: Irsanti Hasyim, Christian Wibisono, Angela Teressia

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Social enterprises, as one of the way of doing business are on the rise and emerging from the innovations of decades of social initiatives. In simple way, social enterprises use the business platform to achieve social and/or environmental objectives whilst simultaneously seeking a financial return. In Indonesia, the number of social enterprises rapidly grows and most of them were using social media as their business platform. Social Media are perceived as tools for creating online communities of users who share interests, activities, and objectives. Many companies view the use of online communities in social media as a profitable marketing tool from which they can derive several benefits. Through social media, consumers share experiences with and suggest ideas to others while developing new relationships within their communities. Therefore, this study intends to identify the benefits that participants in online communities seek and examine the relationships between members’ levels of participation, brand trust, and brand commitment. Using convenience sampling method, 236 fully answered questioner was collected and used as a sample of this research. The sample of this research consisted of member or follower in several social media from selected social enterprise in Indonesia. Data collected in this research were process by using Partial Least Square and came up with the result that functional benefit and monetary benefit, are only two from five benefits that proposed were the only variable that has significant result even though from APC, ARS and AARS outcomes show that the model can be claimed to be significant.

Keywords: brand trust, brand commitment, social enterprise, social media

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Authors: Somayeh Sadat Hashemi Kamangar, Fatemeh Bakouie, Shahriar Gharibzadeh

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In this study, we target to exploit Maximum Spanning Trees (MST) of children's semantic networks to investigate their language development. To do so, we examine the graph-theoretic properties of word-embedding networks. The networks are made of words children learn prior to the age of 30 months as the nodes and the links which are built from the cosine vector similarity of words normatively acquired by children prior to two and a half years of age. These networks are weighted graphs and the strength of each link is determined by the numerical similarities of the two words (nodes) on the sides of the link. To avoid changing the weighted networks to the binaries by setting a threshold, constructing MSTs might present a solution. MST is a unique sub-graph that connects all the nodes in such a way that the sum of all the link weights is maximized without forming cycles. MSTs as the backbone of the semantic networks are suitable to examine developmental changes in semantic network topology in children. From these trees, several parameters were calculated to characterize the developmental change in network organization. We showed that MSTs provides an elegant method sensitive to capture subtle developmental changes in semantic network organization.

Keywords: maximum spanning trees, word-embedding, semantic networks, language development

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