Search results for: minimal social networks

Authors: M. A. T. AlSudairi, T. G. K. Vasista

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The concept of social media is becoming the top of the agenda for many business executives and public sector executives today. Decision makers as well as consultants, try to identify ways in which firms and enterprises can make profitable use of social media and network related applications such as Wikipedia, Face book, YouTube, Google+, Twitter. While it is fun and useful to participating in this media and network for achieving the communication effectively and efficiently, semantic and sentiment analysis and interpretation becomes a crucial issue. So, the objective of this paper is to provide literature review on social media, network and related technology related to semantics and sentiment or opinion analysis covering business and governance perspectives. In this regard, a case study on the use and adoption of Social media in Saudi Arabia has been discussed. It is concluded that semantic web technology play a significant role in analyzing the social networks and social media content for extracting the interpretational knowledge towards strategic decision support.

Keywords: CRASP methodology, formative assessment, literature review, semantic web services, social media, social networks

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Authors: Bojan Najdenov, Danco Davcev

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Reduction of traffic congestions and the effects of pollution and waste of resources that come with them has been a big challenge in the past decades. Having reliable systems to facilitate the process of modeling and prediction of traffic conditions would not only reduce the environmental pollution, but will also save people time and money. Social networks play big role of people’s lives nowadays providing them means of communicating and sharing thoughts and ideas, that way generating huge knowledge bases by crowdsourcing. In addition to that, crowdsourcing as a concept provides mechanisms for fast and relatively reliable data generation and also many services are being used on regular basis because they are mainly powered by the public as main content providers. In this paper we present the Social-NETS-Traffic-Control System (SNTCS) that should serve as a facilitator in the process of modeling and prediction of traffic congestions. The main contribution of our system is to integrate data from social networks as Twitter and also implements a custom created crowdsourcing subsystem with which users report traffic conditions using an android application. Our first experience of the usage of the system confirms that the integrated approach allows easy extension of the system with other social networks and represents a very useful tool for traffic control.

Keywords: traffic, congestion reduction, crowdsource, social networks, twitter, android

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Authors: Yaseein S. Hussein, Victor P. Gil Jiménez, Abdulmajeed Al-Jumaily

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Due to the rapid advancement of technology, there is an increasing demand for wireless connections that are both fast and reliable, with minimal latency. New wireless communication standards are developed every decade, and the year 2030 is expected to see the introduction of 6G. The primary objectives of 6G network and terminal designs are focused on sustainability and environmental friendliness. The International Telecommunication Union-Recommendation division (ITU-R) has established the minimum requirements for 6G, with peak and user data rates of 1 Tbps and 10-100 Gbps, respectively. In this context, Light Fidelity (Li-Fi) technology is the most promising candidate to meet these requirements. This article will explore the various advantages, features, and potential applications of Li-Fi technology, and compare it with 5G networking, to showcase its potential impact among other emerging technologies that aim to enable 6G networks.

Keywords: 6G networks, artificial intelligence (AI), Li-Fi technology, Terahertz (THz) communication, visible light communication (VLC)

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Authors: Jehan Fahim M. Alsulami

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Academic research about sentiment analysis in sentiment analysis has obtained significant advancement over recent years and is flourishing from the collection of knowledge provided by various academic disciplines. In the current study, the status and development trend of the field of sentiment analysis in social networks is evaluated through a bibliometric analysis of academic publications. In particular, the distributions of publications and citations, the distribution of subject, predominant journals, authors, countries are analyzed. The collaboration degree is applied to measure scientific connections from different aspects. Moreover, the keyword co-occurrence analysis is used to find out the major research topics and their evolutions throughout the time span. The area of sentiment analysis in social networks has gained growing attention in academia, with computer science and engineering as the top main research subjects. China and the USA provide the most to the area development. Authors prefer to collaborate more with those within the same nation. Among the research topics, newly risen topics such as COVID-19, customer satisfaction are discovered.

Keywords: bibliometric analysis, sentiment analysis, social networks, social media

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Authors: Ehsan Khademi, Mahdi Jalili

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Despite the special features of bipartite networks, they are common in many systems. Real-world bipartite networks may show community structure, similar to what one can find in one-mode networks. However, the interpretation of the community structure in bipartite networks is different as compared to one-mode networks. In this manuscript, we compare a number of available methods that are frequently used to discover community structure of bipartite networks. These networks are categorized into two broad classes. One class is the methods that, first, transfer the network into a one-mode network, and then apply community detection algorithms. The other class is the algorithms that have been developed specifically for bipartite networks. These algorithms are applied on a model network with prescribed community structure.

Keywords: community detection, bipartite networks, co-clustering, modularity, network projection, complex networks

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Authors: Ourn Vimoil, Kallaya Suntornvongsagul

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Cambodia is considered as one of the most disaster prone countries in South East Asia, and most of natural disasters are related to floods. Cambodia, a developing country, faces significant impacts from floods, such as environmental, social, and economic losses. Using data accessed from focus group discussions and field surveys with villagers in Ba Baong commune, prey Veng province, Cambodia, the research would like to examine roles of social networks in raising community’s coping capacity with floods. The findings indicate that social capital play crucial roles in three stages of floods, namely preparedness, response, and recovery to overcome the crisis. People shared their information and resources, and extent their assistances to one another in order to adapt to floods. The study contribute to policy makers, national and international agencies working on this issue to pay attention on social networks as one factors to accelerate flood coping capacity at community level.

Keywords: social network, community, coping capacity, flood, Cambodia

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Authors: Alireza Alesaadi

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Reliability analysis is a powerful method for determining the weak points of the electrical networks. In designing of electrical network, it is tried to design the most reliable network with minimal system shutting down, but it is usually associated with increasing the cost. In this paper, using adaptive genetic algorithm, a method was presented that provides the most reliable system with a certain economical cost. Finally, the proposed method is applied to a sample network and results will be analyzed.

Keywords: reliability, adaptive genetic algorithm, electrical network, communication engineering

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Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

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Authors: Ladaporn Pithuk

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This study aims to investigate the marketing mixed factors that affecting on expectations about commercial transactions through social networks. The research method will using quantitative research, data was collected by questionnaires to person have experience access to trading over the internet for 400 sample by purposive sampling method. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and using quality function deployment for hypothesis testing. Finding the most significant interrelationship between marketing mixed factors and commercial transactions expectations through social networks are product and place the relationship of five ties product and place (location) is involved in almost all will make the site a model that meets the needs of the user visit. In terms of price, the promotion, privacy, personalization and providing a process technical. This will make operations more efficient, reduce confusion, duplication, delays in data transmission, including the creation of different elements in products and services.

Keywords: commercial transactions expectations, marketing mixed factors, social networks, consumer behavior

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Authors: Mohammad Mehdizadeh

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COVID-19 forced marketers to change their marketing strategies, focusing less on reactive approaches and more on proactive approaches, primarily social media. The next few years will be dominated by employee engagement and customer experience, leading to businesses focusing more on "long-term customer relationships." A large number of marketing strategies need to be employed in an ever-evolving online environment, which is both filled with opportunities and dangers, as well as being an intimidating platform to use, incorporating new and exciting opportunities for businesses and organizations as it constantly evolves. In this article, we examine the effect of social networks on marketing in post-pandemic environments. A descriptive survey is used as the research method. The results show that social networks have a positive and significant impact on marketing in a post-pandemic environment. Among the social networks studied, Instagram, Facebook, and Twitter have the most positive effect on marketing advancement.

Keywords: COVID-19, customers, marketing, post-pandemic

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Authors: Paulu Saramge Shalika Nirupani Seram

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The study delves into the complex dynamics of social networks and how they affect paddy farmers’ adoption of agricultural technologies, which are included in Yaya Development program, Weedy rice program and Good Agricultural Practices (GAP) program in Matara district. Identify the social networks among the farmers of ongoing Extension Programs in Matara district, examine the farmers’ adoption level to the ongoing extension programs in Matara district, analyze the impacts of social networks for the adoption to the technologies of ongoing extension programs and give suggestions and recommendations to improve the social network of paddy farmers in Matara District for ongoing extension programs are the objectives of this research. A structured questionnaire survey was conducted with 25 farmers from Matara-North (Wilpita), 25 farmers from Matara-Central (Kamburupitiya), and 25 farmers from Matara-South (Malimbada). UCINET (Version -6.771) software was used for social network analysis, and other than that, descriptive statistics and inferential statistics were used to analyze the findings. Matara-North has the highest social network density, and Matara-South has the lowest social network density according to the social network analysis. Dissemination of intensive technologies requires the most prominent actors of the social network, and in Matara district, agricultural instructors have the highest ability to disseminate technologies. The influence of actors in the social network, the trustworthiness of AI officers, and the trust of indigenous knowledge about paddy cultivation have a significant effect on the technology adoption of farmers. The research endeavors to contribute a nuanced understanding of the social networks and agricultural technology adoption in Matara District, offering practical insights for stakeholders involved in agricultural extension services.

Keywords: agricultural extension, paddy cultivation, social network, technology adoption

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Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

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Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: big data, social networks, sentiment analysis, twitter

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Authors: Omari W. Keeles

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Attention to social class and race processes could illuminate within- group differences in Black students' experiences that help explain variation in adjustment. Of interest is how social class relates to development of intragroup connections with other Black students on campus in ways that promote or inhibit well-being. The present study’s findings suggest that students from lower class backgrounds may be more restrictive or limited in opportunities around their intragroup friendship networks than more affluent students. Furthermore, Black social relationship networks were related to positive mental health adjustment important to healthy psychological functioning and development.

Keywords: black students, social class, homophily, psychological adjustment

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Authors: Biljana Marković

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Social networks are an integral part of our everyday lives, becoming an indispensable medium for communication in personal and business environments. New forms and ways of communication change the general mindset and significantly affect the quality of life of individuals. Quality of life is perceived as an abstract term, but often people are not aware that they directly affect the quality of their own lives, making minor but significant everyday choices and decisions. Quality of life can be defined broadly, but in the widest sense, it involves a subjective sense of satisfaction with one's life. Scientific knowledge about the impact of social networks on self-assessment of the quality of life of individuals is only just beginning to be researched. Available research indicates potential benefits as well as a number of disadvantages. In the context of the previous claims, the focus of the study conducted by the authors of this paper focuses on analyzing the impact of social networks on individual’s self-assessment of quality of life and the correlation between time spent on social networks, and the choice of content that individuals choose to share to present themselves. Moreover, it is aimed to explain how much and in what ways they critically judge the lives of others online. The research aspires to show the positive as well as negative aspects that social networks, primarily Facebook and Instagram, have on creating a picture of individuals and how they compare themselves with others. The topic of this paper is based on quantitative research conducted on a representative sample. An analysis of the results of the survey conducted online has elaborated a hypothesis which claims that content shared by individuals on social networks influences the image they create about themselves. A comparative analysis of the results obtained with the results of similar research has led to the conclusion about the synergistic influence of social networks on the feeling of the quality of life of respondents. The originality of this work is reflected in the approach of conducting research by examining attitudes about an individual's life satisfaction, the way he or she creates a picture of himself/herself through social networks, the extent to which he/she compares herself/himself with others, and what social media applications he/she uses. At the cognitive level, scientific contributions were made through the development of information concepts on quality of life, and at the methodological level through the development of an original methodology for qualitative alignment of respondents' attitudes using statistical analysis. Furthermore, at the practical level through the application of concepts in assessing the creation of self-image and the image of others through social networks.

Keywords: quality of life, social media, self image, influence of social media

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Authors: Suha Alawadhi, Malak Alrasheed

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In the recent past, public participation in governments has been declined to a great extent, as citizens have been isolated from community life and their ability to articulate demands for good government has been noticeably decreased. However, the Internet has introduced new forms of interaction that could enhance different types of relationships, including government-public relationship. In fact, technology-enabled government has become a catalyst for enabling social inclusion. This exploratory study seeks to investigate public perceptions in Kuwait regarding the use of social media networks in government where social capital is built to achieve social inclusion. Social capital has been defined as social networks and connections amongst individuals, that are based on shared trust, ideas and norms, enable participants of a network to act effectively to pursue a shared objective. The quantitative method was used to generate empirical evidence. A questionnaire was designed to address the research objective and reflect the identified constructs: social capital dimensions (bridging, bonding and maintaining social capital), social inclusion, and social equality. In this pilot study, data was collected from a random sample of 61 subjects. The results indicate that all participants have a positive attitude towards the dimensions of social capital (bridging, bonding and maintaining), social inclusion and social equality constructs. Tests of identified constructs against demographic characteristics indicate that there are significant differences between male and female as they perceived bonding and maintaining social capital, social inclusion and social equality whereas no difference was identified in their perceptions of bridging social capital. Also, those who are aged 26-30 perceived bonding and maintaining social capital, social inclusion and social equality negatively compared to those aged 20-25, 31-35, and 40-above whose perceptions were positive. With regard to education, the results also show that those holding high school, university degree and diploma perceived maintaining social capital positively higher than with those who hold graduate degrees. Moreover, a regression model is proposed to study the effect of bridging, bonding, and maintaining social capital on social inclusion via social equality as a mediator. This exploratory study is necessary for testing the validity and reliability of the questionnaire which will be used in the main study that aims to investigate the perceptions of individuals towards building social capital to achieve social inclusion.

Keywords: government, social capital, social inclusion, social networks

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Authors: Danielle Sandler dos Passos, Helder Coelho, Flávia Mori Sarti

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Complexity science seeks the understanding of systems adopting diverse theories from various areas. Network analysis has been gaining space and credibility, namely with the biological, social and economic systems. Significant part of the literature focuses only monolayer representations of connections among agents considering one level of their relationships, and excludes other levels of interactions, leading to simplistic results in network analysis. Therefore, this work aims to demonstrate the advantages of the use of multilayer networks for the representation and analysis of networks. For this, we analyzed an interbank network, composed of 42 banks, comparing the centrality measures of the agents (degree and PageRank) resulting from each method (monolayer x multilayer). This proved to be the most reliable and efficient the multilayer analysis for the study of the current networks and highlighted JP Morgan and Deutsche Bank as the most important banks of the analyzed network.

Keywords: complexity, interbank networks, multilayer networks, network analysis

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Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi

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Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.

Keywords: social network, link prediction, granular computing, type-2 fuzzy sets

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Authors: Wipada Chaiwchan

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This research aims to study behaviors in using social networks of Corporate personnel of Suan Sunandha Rajabhat University. The sample used in the study were two groups: 1) Academic Officer 70 persons and 2) Operation Officer 143 persons were used in this study. The tools in this research consisted of questionnaire which the data were analyzed by using percentage, average (X) and Standard deviation (S.D.) and Independent Sample T-Test to test the difference between the mean values obtained from two independent samples, and One-way anova to analysis of variance, and Multiple comparisons to test that the average pair of different methods by Fisher’s Least Significant Different (LSD). The study result found that the most of corporate personnel have purpose in using social network to information awareness aspect was knowledge and online conference with social media. By using the average more than 3 hours per day in everyday. Using time in working in one day and there are computers connected to the Internet at home, by using the communication in the operational processes. Behaviors using social networks in relation to gender, age, job title, department, and type of personnel. Hypothesis testing, and analysis of variance for the effects of this analysis is divided into three aspects: The use of online social networks, the attitude of the users and the security analysis has found that Corporate Personnel of Suan Sunandha Rajabhat University. Overall and specifically at the high level, and considering each item found all at a high level. By sorting of the social network (X=3.22), The attitude of the users (X= 3.06) and the security (X= 3.11). The overall behaviors using of each side (X=3.11).

Keywords: social network, behaviors, social media, computer information systems

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Authors: Hirokatsu Kawashima

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In an attempt to elucidate relationships between listening to music and pronunciation learning, a classroom-based investigation was conducted with Japanese EFL learners (n=45). The subjects were instructed to listen to English songs they liked on YouTube, especially paying attention to phonologically similar vowel and consonant minimal pair words (e.g., live and leave). This kind of activity, which included taking notes, was regularly carried out in the classroom, and the same kind of task was given to the subjects as homework in order to reinforce the in-class activity. The duration of these activities was eight weeks, after which the program was evaluated on a 9-point scale (1: the lowest and 9: the highest) by learners’ self-evaluation. The main questions for this evaluation included 1) how good the learners had been at pronouncing vowel and consonant minimal pair words originally, 2) how often they had listened to songs good for pronouncing vowel and consonant minimal pair words, 3) how frequently they had moved their mouths to vowel and consonant minimal pair words of English songs, and 4) how much they thought the program would support and enhance their pronunciation learning of phonologically similar vowel and consonant minimal pair words. It has been found, for example, A) that the evaluation of this program is by no means low (Mean: 6.51 and SD: 1.23), suggesting that listening to music may support and enhance pronunciation learning, and B) that listening to consonant minimal pair words in English songs and moving the mouth to them are more related to the program’s evaluation (r =.69, p=.00 and r =.55, p=.00, respectively) than listening to vowel minimal pair words in English songs and moving the mouth to them (r =.45, p=.00 and r =.39, p=.01, respectively).

Keywords: minimal pair, music, pronunciation, song

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Authors: B. Thanasansomboon, S. Choemprayong, N. Parinyanitikul, U. Tanlamai

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Being diagnosed with metastatic breast cancer, the patients as well as their caretakers are affected physically and mentally. Although the medical systems in Thailand have been attempting to improve the quality and effectiveness of the treatment of the disease in terms of physical illness, the success of the treatment also depends on the quality of mental health. Metastatic breast cancer patients have found that social support is a key factor that helps them through this difficult time. It is recognized that social support in different dimensions, including emotional support, social network support, informational support, instrumental support and appraisal support, are contributing factors that positively affect the quality of life of patients in general, and it is undeniable that social support in various forms is important in promoting the quality of life of metastatic breast patients. However, previous studies have not been dedicated to investigating their quality of life concerning affective, cognitive, and behavioral outcomes. Therefore, this study aims to develop integrated social support through social networks to improve the quality of life of metastatic breast cancer patients in Thailand.

Keywords: social support, metastatic breath cancer, quality of life, social network

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Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

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Authors: Amrah Maryam

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The emergence of online social networks (OSNs) has transformed the way we pursue and share information. On the one hand, OSNs provide great ease for the spreading of positive information while, on the other hand, they may also become a channel for the spreading of malicious rumors and misinformation throughout the social network. Thus, to assure the trustworthiness of OSNs to its users, it is of vital importance to detect the misinformation propagation in the network by placing network monitors. In this paper, we aim to place monitors near the suspected nodes with the intent to limit the diffusion of misinformation in the social network, and then we also detect the most significant nodes in the network for propagating true information in order to minimize the effect of already diffused misinformation. Thus, we initiate two heuristic monitor placement using articulation points and truth propagation using eigenvector centrality. Furthermore, to provide real-time workings of the system, we integrate both the monitor placement and truth propagation entities as well. To signify the effectiveness of the approaches, we have carried out the experiment and evaluation of Stanford datasets of online social networks.

Keywords: online social networks, monitor placement, independent cascade model, spread of misinformation

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Authors: Amir Farouk Ahmed Ali Hussin

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Social media, such as Facebook, LinkedIn and Ex-Twitter have experienced exponential growth and a remarkable adoption rate in recent years. They give fantastic means of online social interactions and communications with family, friends, and colleagues from around the corner or across the globe, and they have become an important part of daily digital interactions for more than one and a half billion users around the world. The personal information sharing practices that social network providers encourage have led to their success as innovative social interaction platforms. Moreover, these practices have outcome in concerns with respect to privacy and security from different stakeholders. Guiding these privacy and security concerns in social networks is a must for these networks to be sustainable. Real security and privacy tools may not be enough to address existing concerns. Some points should be followed to protect users from the existing risks. In this research, we have checked the various privacy and security issues and concerns pertaining to social media. However, we have classified these privacy and security issues and presented a thorough discussion of the effects of these issues and concerns on the future of the social networks. In addition, we have presented a set of points as precaution measures that users can consider to address these issues.

Keywords: international legal, consultation mix, legal research, small and medium-sized enterprises, strategic International law, strategy alignment, house of laws, deployment, production strategy, legal strategy, business strategy

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Authors: Namrata Mishra

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Health of a person plays a vital role in the collective health of his community and hence the well-being of the society as a whole. But, in today’s fast paced technology driven world, health issues are increasingly being associated with human behaviors – their lifestyle. Social networks have tremendous impact on the health behavior of individuals. Many researchers have used social network analysis to understand human behavior that implicates their social and economic environments. It would be interesting to use a similar analysis to understand human behaviors that have health implications. This paper focuses on concepts of those behavioural analyses that have health implications using social networks analysis and provides possible algorithmic approaches. The results of these approaches can be used by the governing authorities for rolling out health plans, benefits and take preventive measures, while the pharmaceutical companies can target specific markets, helping health insurance companies to better model their insurance plans.

Keywords: breadth first search, directed graph, health behaviors, social network analysis

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Authors: Ivan Belik, Kurt Jornsten

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We construct the coauthorship network based on the scientific collaboration between the faculty members at the Norwegian School of Economics (NHH) and based on their international academic publication experience. The network structure is based on the NHH faculties’ publications recognized by the ISI Web of Science for the period 1950 – Spring, 2014. The given network covers the publication activities of the NHH faculty members (over six departments) based on the information retrieved from the ISI Web of Science in Spring, 2014. In this paper we analyse the constructed coauthorship network in different aspects of the theory of social networks analysis.

Keywords: coauthorship networks, social networks analysis, Norwegian School of Economics, ISI

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Authors: Lindy Van Vliet, Saloni Phadke, Anthea Nelson, Ann Gallant

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Comprehensive and compassionate palliative care and support requires an integrated system of care that draws on formal health and social service providers working together with community and informal networks to ensure that patients and families have access to the care they need. The objective of this study is to further explore and understand the community supports, services, and informal networks that health care professionals and social service providers rely on to allow their patients to die in their homes and communities. Drawing on an interpretivist, exploratory, qualitative design, our multidisciplinary research team (medicine, nursing and social work) conducted interviews with 15 health care and social service providers in the Ottawa region. Interview data was audio-recorded, transcribed and analyzed using a reflexive thematic analysis approach. The data deepens our understandings of the facilitators and barriers that arise as health care and social service providers attempt to build networks of care for patients with life limiting illnesses and families. Three main findings emerged: First, the variability that arises due to systemic barriers in accessing and providing care; second, the exceptionally challenging workload that providers are facing as they work to address complex social care needs (housing, disability, food security), along with escalating palliative care needs; and, finally, the lack of structural support that providers and informal care networks receive. Conclusion: These findings will facilitate and build stronger person-centred/relationship-centred principles and practices between providers, patients, community, and informal care networks by highlighting the systemic barriers to accessing and providing person-centred care. Further, they will have important implications for future partnerships in integrated care delivery programs and initiatives, community policies, education programs, and provincial and national palliative care strategies.

Keywords: public health palliative care, palliative care nursing, care networks, informal care, integrated health care

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Authors: Alireza Alesaadi

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Flexible AC transmission system (FACTS) devices have an important rule on expnded electrical transmission networks. In this paper, the effect of these diveces on reliability of electrical networks is studied and it is shown that using of FACTS devices can improve the relibiability of power networks, significantly.

Keywords: FACTS devices, power networks, reliability

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Authors: Balimu Mwiya, Mundia Muya, Chabota Kaliba, Peter Mukalula

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Factors affecting construction unit cost vary depending on a country’s political, economic, social and technological inclinations. Factors affecting construction costs have been studied from various perspectives. Analysis of cost factors requires an appreciation of a country’s practices. Identified cost factors provide an indication of a country’s construction economic strata. The purpose of this paper is to identify the essential factors that affect unit cost estimation and their breakdown using artificial neural networks. Twenty-five (25) identified cost factors in road construction were subjected to a questionnaire survey and employing SPSS factor analysis the factors were reduced to eight. The 8 factors were analysed using the neural network (NN) to determine the proportionate breakdown of the cost factors in a given construction unit rate. NN predicted that political environment accounted 44% of the unit rate followed by contractor capacity at 22% and financial delays, project feasibility, overhead and profit each at 11%. Project location, material availability and corruption perception index had minimal impact on the unit cost from the training data provided. Quantified cost factors can be incorporated in unit cost estimation models (UCEM) to produce more accurate estimates. This can create improvements in the cost estimation of infrastructure projects and establish a benchmark standard to assist the process of alignment of work practises and training of new staff, permitting the on-going development of best practises in cost estimation to become more effective.

Keywords: construction cost factors, neural networks, roadworks, Zambian construction industry

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Authors: John Bankier

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Development of academic English occurs not only in communities of practice but also within wider social networks, referred to by Zappa-Hollman and Duff as individual networks of practice. Such networks may exist whether students are developing academic English in English-dominant contexts or in contexts in which English is not a majority language. As yet, little research has examined how newcomers to universities interact with a variety of social ties in such networks to receive academic and emotional support as they develop the academic English necessary to succeed in local and global academia. The one-year ethnographic study described in this presentation followed five Japanese university students enrolled on an academic English program in their home country. We graphically represent participants’ individual networks of practice related to academic English and display the role of interaction in these networks to socialization. Specific examples of academic practices will be linked to specific instances of social interaction. Interaction supportive of the development of academic practices often occurred during unplanned interactions outside the classroom and among small groups of close friends who were connected to each other in more than one way, such as those taking multiple classes together. These interactions occurred in study spaces, in hallways between class periods, at lunchtimes, and online. However, constraints such as differing accommodation arrangements, class scheduling and the hierarchical levelling of English classes by test scores discouraged some participants both from forming strong ties related to English and from interacting with existing ties. The presentation will briefly describe ways in which teachers in all contexts can maximise interaction outside the classroom.

Keywords: academic, english, practice, network

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Authors: Radhia Toujani, Jalel Akaichi

Abstract:

In recent years, the study of community detection in social networks has received great attention. The hierarchical structure of the network leads to the emergence of the convergence to a locally optimal community structure. In this paper, we aim to avoid this local optimum in the introduced hybrid hierarchical method. To achieve this purpose, we present an objective function where we incorporate the value of structural and semantic similarity based modularity and a metaheuristic namely bees colonies algorithm to optimize our objective function on both hierarchical level divisive and agglomerative. In order to assess the efficiency and the accuracy of the introduced hybrid bee colony model, we perform an extensive experimental evaluation on both synthetic and real networks.

Keywords: social network, community detection, agglomerative hierarchical clustering, divisive hierarchical clustering, similarity, modularity, metaheuristic, bee colony

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