Search results for: social data analysis

Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

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In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: simulation data, data summarization, spatial histograms, exploration, visualization

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Authors: Zebider Asire Munyelet, Yibeltal Chanie Manie

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In the modern digital landscape, the increase of social media platforms has become identical to the evolution of online consumer behavior. This study investigates the complicated relationship between social media and the purchasing decisions of online buyers. Through an extensive review of existing literature and empirical research, the aim is to comprehensively analyze the multidimensional impact that social media exerts on the various stages of the online buyer's journey. The investigation encompasses the exploration of how social media platforms serve as influential channels for information dissemination, product discovery, and consumer engagement. Additionally, the study investigates into the psychological aspects underlying the role of social media in shaping buyer preferences, perceptions, and trust in online transactions. The methodologies employed include both quantitative and qualitative analyses, incorporating surveys, interviews, and data analytics to derive meaningful insights. Statistical models are applied to distinguish patterns in online buyer behavior concerning product awareness, brand loyalty, and decision-making processes. The expected outcomes of this research contribute not only to the academic understanding of the dynamic interplay between social media and online buyer behavior but also offer practical implications for marketers, e-commerce platforms, and policymakers.

Keywords: consumer Behavior, social media, online purchasing, online transaction

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Authors: Barnabás Körmöndi

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The recent crises have affected societies worldwide, resulting in the irresponsible exploitation of natural resources and the unattainability of sustainability. Regions that are economically underdeveloped, such as the Bodrogköz in Eastern Hungary and Slovakia, experience these issues more severely. The aim of this study is to analyze the natural and social resources of the Bodrogköz area for the planning of complex development based on ecotourism. The objective is to develop ecotourism opportunities in this least developed area of the borderland of Hungary and Slovakia. The study utilizes desk research, deep interviews, focus group meetings, and remote sensing methods. Desk research is aimed at providing a comprehensive understanding of the area, while deep interviews and focus group meetings were conducted to understand the stakeholders' perspectives on the potential for ecotourism. Remote sensing methods were used to better understand changes in the natural environment. The study identified the potential for ecotourism development in the Bodrogköz area due to its near-natural habitats along its bordering rivers and rich cultural heritage. The analysis revealed that ecotourism could promote the region's sustainable development, which is essential for its economic growth. Additionally, the study identified the possible threats to the natural environment during ecotourism development and suggested strategies to mitigate these threats. This study highlights the significance of ecotourism in promoting sustainable development in underdeveloped areas such as the Bodrogköz. It provides a basis for future research on ecotourism development and sustainable planning in similar regions. The analysis is based on the data collected through desk research, deep interviews, focus group meetings, and remote sensing. The assessment was conducted through content analysis, which allowed for the identification of themes and patterns in the data. The study addressed the question of how to develop ecotourism in the least developed area of the borderland of Hungary and Slovakia and promote sustainable development in the region. In conclusion, the study highlights the potential for ecotourism development in Bodrogköz and identifies the natural and social resources that contribute to its development. The study emphasizes the need for sustainable development to promote economic growth and mitigate any environmental threats. The findings can inform the development of future strategic plans for ecotourism, promoting sustainable development in underdeveloped regions.

Keywords: ecotourism, natural resources, remote sensing, social development

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Authors: Julide Yildirim, Nadir Ocal

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Even though there are many studies investigating the extent and determinants of poverty, there is paucity of research investigating the issue of energy poverty in Turkey. The aim of this paper is threefold: First to investigate the extend of energy poverty in Turkey by using Household Budget Survey datasets belonging to 2005 - 2016 period. Second, to examine the risk factors for energy poverty. Finally, to assess the impact of social assistance program participation on energy poverty. Existing literature employs alternative methods to measure energy poverty. In this study energy poverty is measured by employing expenditure approach, where people are considered as energy poor if they disburse more than 10 per cent of their income to meet their energy requirements. Empirical results indicate that energy poverty rate is around 20 per cent during the time period under consideration. Since Household Budget Survey panel data is not available for 2005 - 2016 period, a pseudo panel has been constructed. Panel logistic regression method is utilized to determine the risk factors for energy poverty. The empirical results demonstrate that there is a statistically significant impact of work status and education level on energy poverty likelihood. In the final part of the paper the impact of social transfers on energy poverty has been examined by utilizing panel biprobit model, where social transfer participation and energy poverty incidences are jointly modeled. The empirical findings indicate that social transfer program participation reduces energy poverty. The negative association between energy poverty and social transfer program participation is more pronounced in urban areas compared with the rural areas.

Keywords: energy poverty, social transfers, panel data models, Turkey

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Authors: Debalina Datta, Pratyaypratim Datta, Kunal Kanti Majumdar

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Introduction: In India 8.1% of total population is elderly. The standard of living and meaningfulness of life are indirectly measured by assessing quality of life of elderly. So, it is important to improve quality of life. Quality of life is an individual’s understanding of his/ her life situation with respect to his/ her values and cultural context as well as in relation to his/her goals, expectations and concerns. The present study was planned to assess the quality of life of geriatric people in urban West Bengal, India. Materials and methods: It was a community based cross sectional observational study conducted among people aged 60 years and above in Kolkata and Sonarpur region of West Bengal, India. Data collection was done by house to house visit using Quality of Life- BREF questionnaire (WHOQOL-BERF) developed by WHO. Analysis of quality of life of physical, psychological, social relationship and environmental domain was done using SPSS (version 16.0). Results: Transformed score (0-100 scale) was used for each domain. Mean of physical, psychological, social relationship and environmental domain were found to be 42.25, 40.84, 39.62 and 48.36 respectively. There was no significant difference in score between Kolkata and Sonarpur people in any domain except social relationship domain, where people living at Sonarpur scored significantly better. Conclusion: Rehabilitation of old age people can be done by improving their quality of life. Social interaction with people of all ages, allowing them to take important family decision, engaging them in different social activities can help a lot.

Keywords: quality of life, elderly, Urban West Bengal, India

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Authors: Bashaiar Al-Sanaa

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Class has always been a vital distinguishing factor among people within any society. Clear borders between social layers; such as royals, nobles, aristocrats, the bourgeoisie, and working class; have been minimized and blurred due to the advent of social media. Unprecedented access to information has played a significant role in teaching different individuals about the nature of other social layers, hence, allowing for imitation and integration. This study aims to fill the void in research conducted on such topic. The research explores how social media may be slowly but surely dissolving apparent and rigid borderlines of social class. In order to present an overview of the topic, the study surveys individuals in Kuwait to measure how using social media changed their views and style of social class. It also draws a framework through which implications and suggestions for future research may be discussed to better serve the advancement of human communication.

Keywords: class, communication, Kuwait, social media

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Authors: Kelsi Matwick, Keri Matwick

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This presentation focuses on national campaigns as a government tactic of social behavior and order. Focusing on one of Singapore’s first national campaigns, Keep Singapore Clean (1968), particularly its iterations of public hygiene in recent years: Keep the Toilets Clean (2012-2019) and UnLittering with Mary Chongo (2019), the study examines how humor and the use of multimodality reflect contemporary practices in political practice. A critical social semiotic analysis involving the textual (linguistic and visual design) and material (print cartoons and videos) is undertaken to show how these messages are communicated. Incongruity and parody are humorous mechanisms used to project the government as likeable, effectively capture the public attention, and instill individual responsibility for the greater community. In focusing on public hygiene national campaigns, the study further illustrates how humor offers a polite way to address crude behavior while providing models of exemplary behavior.

Keywords: communication strategies, critical social semiotics, humor, national campaigns

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Authors: Paula M. Lantz

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In the United States, significant socioeconomic and racial inequalities exist in many population-based indicators of health and social welfare. Although a number of effective prevention programs and interventions are available, local and state governments often do not pursue prevention in the face of budgetary constraints and more acute problems. There is growing interest in and excitement about Pay for Success” (PFS) strategies, also referred to as social impact bonds, as an approach to financing and implementing promising prevention programs and services that help the public sector either save money or achieve greater value for an investment. The PFS finance model implements evidence-based interventions using capital from investors who only receive a return on their investment from the government if agreed-upon, measurable outcomes are achieved. This paper discusses the current landscape regarding social impact bonds in the U.S., and their potential and challenges in addressing serious health and social problems. The paper presents an analysis of a number of social science issues that are fundamental to the potential for social impact bonds to successfully address social inequalities in health and social welfare. This includes: a) the economics of the intervention and a potential public payout; b) organizational and management issues in intervention implementation; c) evaluation research design and methods; d) legal/regulatory issues in public payouts to investors; e) ethical issues in the design of social impact bond deals and their evaluation; and f) political issues. Despite significant challenges in the U.S. context, there is great potential for social impact bonds as a type of social impact investing to encourage private investments in evidence-based interventions that address important public health and social problems in underserved populations and provide a return on investment.

Keywords: pay for success, public/private partnerships, social impact bonds, social impact investing

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Authors: Priyadarshini Kiran, Gulshan Kumar

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: Social media are becoming the most important tools for interaction among learners, pedagogues and parents where everybody can share, exchange, comment, discuss and create information and knowledge in a collaborative way. The present case study attempts to highlight the role of social media (WhatsApp) in nurturing learning habits in toddlers with the help of parents in primary education. The Case study is based on primary data collected from a primary school situated in a small town in the northern state of Uttar Pradesh, India. In research methodology, survey and structured interviews have been used as a tool collected from parents and pedagogues. The findings Suggest: - To nurture learning habits in toddlers, parents and pedagogues use social media site (WhatsApp) in real-time and that too is convenient and handy; - Skill enhancement on the part of Pedagogues as a result of employing innovative teaching-learning techniques; - Social media sites serve as a social connectivity tool to ward off negativity and monotony on the part of parents and pedagogues in the wake of COVID- 19

Keywords: innovative teaching-learning techniques, pedagogues, social media, nurture, toddlers

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Authors: Godswill Nwabuisi Osuafor, Sonto Maria Maputle

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Background: Abounding studies found that religiosity and social factors modulate alcohol use among university students. However, there is a scarcity of empirical studies examining the protective effects of religiosity and other social factors on alcohol use and abuse in South African universities. The aim of this study was therefore to assess the protective effects of religiosity and roles of social factors on alcohol use among university students. Methodology: A survey on the use of alcohol among 416 university students was conducted using structured questionnaire in 2014. Data were sourced on religiosity and contextual variables. Students were classified as practicing intrinsic religiosity or extrinsic religiosity based on the response to the measures of religiosity. Descriptive, chi square and binary logistic analyses were used in processing the data. Result: Results revealed that alcohol use was associated with religiosity, religion, sex, family history of alcohol use and experimenting with alcohol. Reporting alcohol abuse was significantly predicted by sex, family history of alcohol use and experimenting with alcohol. Religiosity mediated lower alcohol use whereas family history of alcohol use and experimenting with alcohol promoted alcohol use and abuse. Conclusion: Families, religious groups and societal factors may be the specific niches for intervention on alcohol use among university students.

Keywords: religiosity, alcohol use, protective factors, university students

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Authors: Kasmaoui Kamal, Makhlouf farid

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This article seeks to assess the role of the level of interpersonal trust in a country in the remittance landscape. Using historical data from the 2010-2014 wave of the World Value Survey (WVS) for interpersonal trust, our findings underline the substitution role played by the interpersonal trust with remittances. More accurately, remittances tend to drop when the rate of interpersonal trust in the country of origin is high. Overall, a rise in trust is likely to underpin social cohesion, limiting, therefore, the need for remittances. These results are still fairly solid and unambiguous after controlling for confounding factors and possible reverse causality.

Keywords: interpersonal trust, remittances, social capital, social cohesion

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Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

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The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

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Authors: Adji Achmad Rinaldo Fernandes

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SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.

Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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Authors: Hyun-Woo Cho

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Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

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Authors: Ghazal Doostmohammadi, Susan Rahimzadeh

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Aim: This research aimed to investigate the relationship between empathy and interpersonal trust and recognize the mediating role of loneliness between them in both genders. Methods: With a correlational descriptive design, 192 university students (130 female and 62 male) responded to the questionnaires on “empathy quotient,” “loneliness,” and “interpersonal trust” tests. These tests were designed and validated by experts in the field. Data were analysed using Pearson correlation and path analysis, which is a statistical technique that uses standard linear regression equations to determine the degree of conformity of a theoretical causal model with reality. Results: The data analysis showed that there was no significant correlation between interpersonal trust, both with loneliness (t=0.169) and empathy (t=0.186), while there was a significant negative correlation (t=0.359) between empathy and loneliness. This means that there is an inverse correlation between empathy and loneliness. The path analysis confirmed the hypothesis of the research about the mediating role of loneliness between empathy and interpersonal trust. But gender did not play a role in this relationship. Conclusion: As an outcome, clinical professionals and education trainers should pay more attention to interpersonal trust as a basic need and try to recreate and shape it to prevent people's social breakdown, and on the other hand, self-disclosure training (especially in Men), expression of feelings and courage should be given double importance to prevent the consequences of loneliness.

Keywords: empathy, loneliness, interpersonal trust, gender

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Authors: Abdel-Aziz M. Mohamed, Nermeen Coutry

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Lead time is an important measure of supply chain performance. It impacts both customer satisfactions as well as the total cost of inventory. This paper presents the result of a study on the analysis of the customer order lead-time for a multinational company. In the study, the lead time was divided into three stages: order entry, order fulfillment, and order delivery. A sample of size 2,425 order lines from the company records were considered for this study. The sample data includes information regarding customer orders from the time of order entry until order delivery. Data regarding the lead time of each sage for different orders were also provided. Summary statistics on lead time data reveals that about 30% of the orders were delivered after the scheduled due date. The result of the multiple linear regression analysis technique revealed that component type, logistics parameter, order size and the customer type have significant impact on lead time. Data analysis on the stages of lead time indicates that stage 2 consumes over 50% of the lead time. Pareto analysis was made to study the reasons for the customer order delay in each of the 3 stages. Recommendation was given to resolve the problem.

Keywords: lead time reduction, customer satisfaction, service quality, statistical analysis

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Authors: Elizabeth M. Seabrook, Nikki S. Rickard

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Examining time-dependent measures of emotion such as variability, instability, and inertia, provide critical and complementary insights into mental health status. Observing changes in the pattern of emotional expression over time could act as a tool to identify meaningful shifts between psychological well- and ill-being. From a practical standpoint, however, examining emotion dynamics day-to-day is likely to be burdensome and invasive. Utilizing social media data as a facet of lived experience can provide real-world, temporally specific access to emotional expression. Emotional language on social media may provide accurate and sensitive insights into individual and community mental health and well-being, particularly with focus placed on the within-person dynamics of online emotion expression. The objective of the current study was to examine the dynamics of emotional expression on the social network platform Facebook for active users and their relationship with psychological well- and ill-being. It was expected that greater positive and negative emotion variability, instability, and inertia would be associated with poorer psychological well-being and greater depression symptoms. Data were collected using a smartphone app, MoodPrism, which delivered demographic questionnaires, psychological inventories assessing depression symptoms and psychological well-being, and collected the Status Updates of consenting participants. MoodPrism also delivered an experience sampling methodology where participants completed items assessing positive affect, negative affect, and arousal, daily for a 30-day period. The number of positive and negative words in posts was extracted and automatically collated by MoodPrism. The relative proportion of positive and negative words from the total words written in posts was then calculated. Preliminary analyses have been conducted with the data of 9 participants. While these analyses are underpowered due to sample size, they have revealed trends that greater variability in the emotion valence expressed in posts is positively associated with greater depression symptoms (r(9) = .56, p = .12), as is greater instability in emotion valence (r(9) = .58, p = .099). Full data analysis utilizing time-series techniques to explore the Facebook data set will be presented at the conference. Identifying the features of emotion dynamics (variability, instability, inertia) that are relevant to mental health in social media emotional expression is a fundamental step in creating automated screening tools for mental health that are temporally sensitive, unobtrusive, and accurate. The current findings show how monitoring basic social network characteristics over time can provide greater depth in predicting risk and changes in depression and positive well-being.

Keywords: emotion, experience sampling methods, mental health, social media

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Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

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As Indo-Pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

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Authors: Filip Majetić, Dražen Šimleša, Jelena Puđak, Anita Bušljeta Tonković, Svitlana Pinchuk

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This paper focuses on the self-sustainability aspect of social entrepreneurship (SE). We define SE as a form of entrepreneurship that is social/ecological mission oriented. It means SE organizations start and run businesses and use them to accomplish their social/ecological missions i.e. to solve social/ecological problems or fulfill social/ecological needs. Self-sustainability is defined as the capability of an SE organization to operate by relying on the money earned through trading its products in the free market. For various reasons, the achievement of self-sustainability represents a fundamental (business) challenge for many SE organizations. Those that are not able to operate using the money made through commercial activities, in order to remain active, rely on alternative, non-commercial streams of income such as grants, donations, and public subsidies. Starting from this widespread (business) challenge, we are interested in exploring elements that (could) influence the self-sustainability in SE organizations. Therefore, the research goal is to empirically investigate some of the self-sustainability factors of two notable SE organizations from different socio-economic contexts. A qualitative research, using the multiple case study approach, was conducted. ACT Group Čakovec (ACT) from Croatia was selected for the first case because it represents one of the leading and most self-sustainable SE organization in the region (in 2015 55% of the organization’s budget came from commercial activities); Friskis&Svettis Stockholm (F&S) from Sweden was selected for the second case because it is a rare example of completely self-sustainable SE organization in Europe (100% of the organization’s budget comes from commercial activities). The data collection primarily consists of conducting in-depth interviews. Additionally, the content of some of the organizations' official materials are analyzed (e.g. business reports, marketing materials). The interviewees are selected purposively and include: six highly ranked F&S members who represent five different levels in the hierarchy of their organization; five highly ranked ACT members who represent three different levels in the hierarchy of the organization. All of the interviews contain five themes: a) social values of the organization, b) organization of work, c) non-commercial income sources, d) marketing/collaborations, and e) familiarity with the industry characteristics and trends. The gathered data is thematically analyzed through the coding process for which Atlas.ti software for qualitative data analysis is used. For the purpose of creating thematic categories (codes), the open coding is used. The research results intend to provide new theoretical insights on factors of SE self-sustainability and, preferably, encourage practical improvements in the field.

Keywords: Friskis&Svettis, self-sustainability factors, social entrepreneurship, Stockholm

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Authors: Sabina Akter, Osiris Valdez Banda, Pentti Kujala, Jani Romanoff

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This paper examines the relationship between on-board environmental factors and customer overall satisfaction in the context of the cruise on-board experience. The on-board environmental factors considered are ambient, layout/design, social, product/service and on-board enjoyment factors. The study presents a data-driven framework and model for the on-board cruise experience. The data are collected from 893 respondents in an application of a self-administered online questionnaire of their cruise experience. This study reveals the cruise passengers’ on-board experience through the customer decision journey based on the publicly available data. Pearson correlation and regression analysis have been applied, and the results show a positive and a significant relationship between the environmental factors and on-board experience. These data help understand the cruise passengers’ on-board experience, which will be used for the ultimate decision-making process in cruise ship design.

Keywords: cruise behavior, customer activities, on-board environmental factors, on-board experience, user or customer satisfaction

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Authors: Yvonne Dedzo

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Social media has become a powerful tool in bridging the distance between individuals regardless of their location. It has become a convenient platform for public discussion and, consequently, generated the phenomenon of citizen journalists who have become both proactive and reactive participants in the dissemination of news, information and other epochal and historical events. This phenomenon has fueled the growth of niche authorities who deliver exceptional democratically consequential information online. This study, therefore, investigates how some selected niche authorities maintain their status on social media. Using the selective processes theory, the study further interrogates the information shared by niche authorities and further analyses the extent to which a public interest-altruistic motive or personal interest-self-serving motive drives their agenda of new sharing and usage. Through cyber-ethnography and, qualitative content analysis and semi-structured interviews, data was gathered and analysed from the posts of two purposely selected niche authorities on Facebook and Twitter. The findings indicate that niche authorities maintain their status by being consistent, prompt, informative, resourceful and interactive in their postings on the social media platform. The study also discovered that even though niche authorities are motivated by both public interest-altruism and interest-self-serving, the latter had a higher of motivation than the former.

Keywords: social medida, citizen journalist, niche authorities, selective processes theory

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Authors: Pamela-Zoe Topalli, Niina Junttila, Päivi M. Niemi, Klaus Ranta

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Adolescents’ biased perceptions about their social competence (SC), whether negatively or positively, serve to influence their socioemotional adjustment such as early feelings of social phobia (nowadays referred to as Social Anxiety Disorder-SAD). Despite the importance of biased self-perceptions in adolescents’ psychosocial adjustment, the extent to which discrepancies between self- and others’ evaluations of one’s SC are linked to social phobic symptoms remains unclear in the literature. This study examined the perceptual discrepancy profiles between self- and peers’ as well as between self- and teachers’ evaluations of adolescents’ SC and the interrelations of these profiles with self-reported social phobic symptoms. The participants were 390 3^rd graders (15 years old) of Finnish lower secondary school (50.8% boys, 49.2% girls). In contrast with variable-centered approaches that have mainly been used by previous studies when focusing on this subject, this study used latent profile analysis (LPA), a person-centered approach which can provide information regarding risk profiles by capturing the heterogeneity within a population and classifying individuals into groups. LPA revealed the following five classes of discrepancy profiles: i) extremely negatively biased perceptions of SC, ii) negatively biased perceptions of SC, iii) quite realistic perceptions of SC, iv) positively biased perceptions of SC, and v) extremely positively biased perceptions of SC. Adolescents with extremely negatively biased perceptions and negatively biased perceptions of their own SC reported the highest number of social phobic symptoms. Adolescents with quite realistic, positively biased and extremely positively biased perceptions reported the lowest number of socio-phobic symptoms. The results point out the negatively and the extremely negatively biased perceptions as possible contributors to social phobic symptoms. Moreover, the association of quite realistic perceptions with low number of social phobic symptoms indicates its potential protective power against social phobia. Finally, positively and extremely positively biased perceptions of SC are negatively associated with social phobic symptoms in this study. However, the profile of extremely positively biased perceptions might be linked as well with the existence of externalizing problems such as antisocial behavior (e.g. disruptive impulsivity). The current findings highlight the importance of considering discrepancies between self- and others’ perceptions of one’s SC in clinical and research efforts. Interventions designed to prevent or moderate social phobic symptoms need to take into account individual needs rather than aiming for uniform treatment. Implications and future directions are discussed.

Keywords: adolescence, latent profile analysis, perceptual discrepancies, social competence, social phobia

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Authors: Nkongho Ayuketang Arreyndip, Ebobenow Joseph

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In this paper, temperature extremes are forecast by employing the block maxima method of the generalized extreme value (GEV) distribution to analyse temperature data from the Cameroon Development Corporation (CDC). By considering two sets of data (raw data and simulated data) and two (stationary and non-stationary) models of the GEV distribution, return levels analysis is carried out and it was found that in the stationary model, the return values are constant over time with the raw data, while in the simulated data the return values show an increasing trend with an upper bound. In the non-stationary model, the return levels of both the raw data and simulated data show an increasing trend with an upper bound. This clearly shows that although temperatures in the tropics show a sign of increase in the future, there is a maximum temperature at which there is no exceedance. The results of this paper are very vital in agricultural and environmental research.

Keywords: forecasting, generalized extreme value (GEV), meteorology, return level

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Authors: Amal Hussain Alkhaiwani, Ghadah Abdullah Almalki

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Recently human errors have increasingly become a very high factor in security breaches that may affect confidential data, and most of the cyber data breaches are caused by human errors. With one individual mistake, the attacker will gain access to the entire network and bypass the implemented access controls without any immediate detection. Unaware employees will be vulnerable to any social engineering cyber-attacks. Providing security awareness to People is part of the company protection process; the cyber risks cannot be reduced by just implementing technology; the human awareness of security will significantly reduce the risks, which encourage changes in staff cyber-awareness. In this paper, we will focus on Human Awareness, human needs to continue the required security education level; we will review human errors and introduce a proposed solution to avoid the breach from occurring again. Recently Saudi Arabia faced many attacks with different methods of social engineering. As Saudi Arabia has become a target to many countries and individuals, we needed to initiate a defense mechanism that begins with awareness to keep our privacy and protect the confidential data against possible intended attacks.

Keywords: cybersecurity, human aspects, human errors, human mistakes, security awareness, Saudi Arabia, security program, security education, social engineering

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Authors: Sarthak Deshpande, Akshay Patil, Pradip Pandhare, Nikhil Wankhede, Rushali Deshmukh

Abstract:

Among the highly significant duties for any language most effective is the sentiment analysis, which is also a key area of NLP, that recently made impressive strides. There are several models and datasets available for those tasks in popular and commonly used languages like English, Russian, and Spanish. While sentiment analysis research is performed extensively, however it is lagging behind for the regional languages having few resources such as Hindi, Marathi. Marathi is one of the languages that included in the Indian Constitution’s 8th schedule and is the third most widely spoken language in the country and primarily spoken in the Deccan region, which encompasses Maharashtra and Goa. There isn’t sufficient study on sentiment analysis methods based on Marathi text due to lack of available resources, information. Therefore, this project proposes the use of different ML/NLP models for the analysis of Marathi data from the comments below YouTube content, tweets or Instagram posts. We aim to achieve a short and precise analysis and summary of the related data using our dataset (Dates, names, root words) and lexicons to locate exact information.

Keywords: multilingual sentiment analysis, Marathi, natural language processing, text summarization, lexicon-based approaches

Procedia PDF Downloads 74

Authors: Musab Isah

Abstract:

This paper presents a longitudinal analysis of Internet speed data in the Gulf Cooperation Council (GCC) region, focusing on the most populous cities of each of the six countries – Riyadh, Saudi Arabia; Dubai, UAE; Kuwait City, Kuwait; Doha, Qatar; Manama, Bahrain; and Muscat, Oman. The study utilizes data collected from the Measurement Lab (M-Lab) infrastructure over a five-year period from January 1, 2019, to December 31, 2023. The analysis includes downstream and upstream throughput data for the cities, covering significant events such as the launch of 5G networks in 2019, COVID-19-induced lockdowns in 2020 and 2021, and the subsequent recovery period and return to normalcy. The results showcase substantial increases in Internet speeds across the cities, highlighting improvements in both download and upload throughput over the years. All the GCC countries have achieved above-average Internet speeds that can conveniently support various online activities and applications with excellent user experience.

Keywords: internet data science, internet performance measurement, throughput analysis, internet speed, measurement lab, network diagnostic tool

Procedia PDF Downloads 63

Authors: Ali Maksum

Abstract:

In a number of countries, including Indonesia, the tendency for non-communicable diseases is increasing. As a result, health costs must be paid by the state continues to increase as well. People's lifestyles, including due to lack of physical activity, are thought to have contributed significantly to the problem. This study aims to examine the impact of participation in sports on quality of life, which is reflected in three main indicators, namely health, psychological, and social aspects. The study was conducted in the city of Surabaya and its surroundings, with a total of 490 participants, consisting of 245 men and 245 women with an average age of 45.4 years. Data on physical activity and quality of life were collected by questionnaire and analyzed using structural equation modeling. The test results of the model prove that the value of chi-square = 8,259 with p = .409, RMSEA = .008, NFI = .992, and CFI = 1. This means that the model is compatible with the data. The model explains that physical activity has a significant effect on quality of life. People who exercise regularly are better able to cope with stress, have a lower risk of illness, and have higher pro-social behavior. Therefore, it needs serious efforts from stakeholders, especially the government, to create an ecosystem that allows the growth of movement culture in the community.

Keywords: participation, physical activity, quality of life, structural equation modelling

Procedia PDF Downloads 124

Authors: Jungeun Cho

Abstract:

Social finance has received increasing attention as a means to promote the growth of regional economies. Despite the plenty of research discussed their critical role and functions in regional economic development such as the financing and promotion of co-operatives or social enterprises and the offering credit to the financially excluded in the region, however, rarely are efforts made to measure the contribution of social finance in the regional economy. It is essential to establish an evaluation model in order to encourage social finance institutions to perform their supposed role and functions on regional economic development. The objective of this paper is to formulate an evaluation model of the contribution of social finance to the regional economy through an analytic hierarchy process (AHP) approach. This study is expected to provide useful guidelines for social finance institutions’ strategies and the policies of local or central government regarding social finance.

Keywords: social finance, regional economy, social economy, policies of local or central government

Procedia PDF Downloads 433

Authors: Eui Jun Jeong, Hye Rim Lee, Ji Hye Yoo

Abstract:

Recent studies have verified the significant relationship of user personality with Internet use. However, in game studies, little research has emphasized on the effects of personality traits on game addiction. This study examined whether big five personality traits affect game addiction with control of psychological, social, and demographic factors. Specifically, using data from a survey of 789 game users in Korea, we conducted a regression analysis to see the associations of psychological (loneliness/depression), social (activities with family/friends), self-efficacy (game/general), gaming (daily gaming time/perception), demographic (age/gender), and personality traits (extraversion, neuroticism conscientiousness, agreeableness, & openness) with the degree of game addiction. Results showed that neuroticism increase game addiction with no effect of extraversion on the addiction. General self-efficacy negatively affected game addiction, whereas game self-efficacy increased the degree of game addiction. Loneliness enhanced game addiction while depression showed a negative effect on the addiction. Results and implications are discussed.

Keywords: game addiction, big five personality, social activities, self-efficacy, loneliness, depression

Procedia PDF Downloads 569