Search results for: social information

Authors: Peggy S. C. van Teunenbroek

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Recently, philanthropic crowd-funding -the raising of external funding from a large audience via social networks or social media- emerged as a new funding instrument for the Dutch cultural sector. However, such philanthropic crowdfunding in the US and the Netherlands is less successful than any other form of crowdfunding. We argue that social aspects are an important stimulus in philanthropic crowd-funding since previous research has shown that crowdfunding is stimulated by something beyond financial merits. Put simply, crowd-funding seems to be a socially motivated activity. In this paper we focus on the effect of social information, described as information about the donation behavior of previous donors. Using a classroom experiment we demonstrated a positive effect of social information on the donation behavior in crowdfunding campaigns. Our study extends previous research by showing who is affected by social information and why, and highlights how social information can be used to stimulate individuals to donate more to crowdfunding projects.

Keywords: online donation behavior, philanthropic crowdfunding, social information, social influence, social motivation

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Authors: Arshia Ayoub, Zahid Ashraf Wani

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With the introduction of online social Q&A sites, people are able to reach each other efficiently for information seeking and simultaneously creating social bonds. There prevails an issue of low or no response for some questions posed by an information seeker on these sites. So this study tries to understand the effect of question type on responses in Social Q & A sites. The study found that among the answered queries, majority of them were answered within 24 hours of posting the questions and surprisingly most replies were received within one hour of posting. It was observed that questions of general information type were most likely to be answered followed by verification type.

Keywords: community‐based services, information seeking, social search, social Q&A site

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Authors: Sanaz Kavianpour, Zuraini Ismail, Bharanidharan Shanmugam

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Social Network Sites (SNSs) can be served as an invaluable platform to transfer the information across a large number of individuals. A substantial component of communicating and managing information is to identify which individual will influence others in propagating information and also whether dissemination of information in the absence of social signals about that information will be occurred or not. Classifying the final audience of social data is difficult as controlling the social contexts which transfers among individuals are not completely possible. Hence, undesirable information diffusion to an unauthorized individual on SNSs can threaten individuals’ privacy. This paper highlights the information diffusion in SNSs and moreover it emphasizes the most significant privacy issues to individuals of SNSs. The goal of this paper is to propose a privacy-preserving model that has urgent regards with individuals’ data in order to control availability of data and improve privacy by providing access to the data for an appropriate third parties without compromising the advantages of information sharing through SNSs.

Keywords: anonymization algorithm, classification algorithm, information diffusion, privacy, social network sites

Procedia PDF Downloads 285

Authors: Rashmi Raghunandan, Sanjana Shankar, Rakshitha K. Bhat

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Social media contributes a vast amount of data and information about individuals to the internet. This project will greatly reduce the need for unnecessary manual analysis of large and diverse social media profiles by filtering out and combining the useful information from various social media profiles, eliminating irrelevant data. It differs from the existing social media aggregators in that it does not provide a consolidated view of various profiles. Instead, it provides consolidated INFORMATION derived from the subject’s posts and other activities. It also allows analysis over multiple profiles and analytics based on several profiles. We strive to provide a query system to provide a natural language answer to questions when a user does not wish to go through the entire profile. The information provided can be filtered according to the different use cases it is used for.

Keywords: social network, analysis, Facebook, Linkedin, git, big data

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Authors: Ritesh Kumar, Rajendra Pamula

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In this paper, we present our contribution for book recommendation. In our experiment, we combine the results of Sequential Dependence Model (SDM) and exploitation of book information such as reviews, tags and ratings. This social information is assigned by users. For this, we used CLEF-2016 Social Book Search Track Suggestion task. Finally, our proposed method extensively evaluated on CLEF -2015 Social Book Search datasets, and has better performance (nDCG@10) compared to other state-of-the-art systems. Recently we got the good performance in CLEF-2016.

Keywords: sequential dependence model, social information, social book search, query expansion

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Authors: Xin-Hua Zhao

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In recent years, the growth rate of social responsibility reports disclosed by Chinese corporations has grown rapidly. The economic effects of the growing corporate social responsibility reports have become a hot topic. The article takes the chemical listed engineering corporations that disclose social responsibility reports in China as a sample, and based on the information asymmetry theory, examines the economic effect generated by corporate social responsibility disclosure with the method of ordinary least squares. The research is conducted from the perspective of analysts’ earnings forecasts and studies the impact of corporate social responsibility information disclosure on improving the accuracy of analysts' earnings forecasts. The results show that there is a statistically significant negative correlation between corporate social responsibility disclosure index and analysts’ earnings forecast error. The conclusions confirm that enterprises can reduce the asymmetry of social and environmental information by disclosing social responsibility reports, and thus improve the accuracy of analysts’ earnings forecasts. It can promote the effective allocation of resources in the market.

Keywords: analysts' earnings forecasts, corporate social responsibility disclosure, economic effect, information asymmetry

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Authors: Sasiphan Nitayaprapha

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A commercially-supported social network has become an emerging channel for an organization to communicate with and provide services to customers. The success of the commercially-supported social network depends on the ability of the organization to keep the customers in participating in the network. Drawing from the theories of information adoption, information systems continuance, and web usability, the author develops a model to explore how a commercially-supported social network can encourage customers to continue participating and using the information in the network. The theoretical model will be proved through an online survey of customers using the commercially-supported social networking sites of several high technology companies operating in the same sector. The result will be compared with previous studies to learn about the explanatory power of the research model, and to identify the main factors determining users’ intention to continue using a commercially-supported social network. Theoretical and practical implications, and limitations are discussed.

Keywords: social network, information adoption, information systems continuance, web usability, user satisfaction

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Authors: Ismail Sualman, Mohd Khairuddin Othman

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General Election has been the backbone of democracy that permits people to choose their representatives as they deem fit. The support preferences of the voter differ from one to another, particularly in a plural society like Malaysia. The turning up of high numbers of young voters during the Malaysia 14th General Election has been said to have been caused by social media including Facebook, Twitter, WhatsApp, Instagram, YouTube and Telegram, WeChat and SMS/MMs. It has been observed that, besides using social media as an interaction tool among social friends, it is also an important source of information to know about issues, politics and politicians. This paper exhibits the role of social media in providing political information to young voters, before an election and during the election campaign. This study examines how this information is being translated into election support. A total of 799 Malay young respondents in Selangor have been surveyed and interviewed. This study revealed that social media has become the source of political information among Malay young voters. This research suggested that social media had a significant effect on the support during the election. Social media plays an important role in carrying information such as current issues, voting trends, candidate imagery and matters that may influence the view of young voters. The information obtained from social media has been translated into a voting decision.

Keywords: social media, political behaviour, voters’ choice, election.

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Authors: Abrar Al-Hasan

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Web 2.0 has significantly increased the amount of information available to users not only about firms and their offerings, but also about the activities of other individuals in their networks and markets. It is widely acknowledged that this increased availability of ‘social’ information, particularly about other individuals, is likely to influence a user’s behavior and choices. However, there are very few systematic studies of how such increased information transparency on the behavior of other users in a focal users’ network influences a focal users’ behavior in the emerging marketplace of online language learning. This study seeks to examine the value and impact of ‘social activities’ – wherein, a user sees and interacts with the learning activities of her peers – on her language learning efficiency. An online experiment in a peer-to-peer language marketplace was conducted to compare the learning efficiency of users with ‘social’ information versus users with no ‘social’ information. The results of this study highlight the impact and importance of ‘social’ information within the language learning context. The study concludes by exploring how these insights may inspire new developments in online education.

Keywords: e-Learning, language learning marketplace, peer-to-peer, social network

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Authors: Yu Hung Chiang, Hei Chia Wang

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In the academic area, it is important for research to find proper research domain. Many researchers may refer to conference issues to find their interesting or new topics. Furthermore, conferences issues can help researchers realize current research trends in their field and learn about cutting-edge developments in their specialty. However, online published conference information may widely be distributed; it is not easy to be concluded. Many researchers use search engine of journals or conference issues to filter information in order to get what they want. However, this search engine has its limitation. There will still be some issues should be considered; i.e. researchers cannot find the associated topics which may be useful information for them. Hence, use Knowledge Management (KM) could be a way to resolve these issues. In KM, ontology is widely adopted; but most existed ontology construction methods do not consider social information between target users. To effective in academic KM, this study proposes a method of constructing research Topic Maps using Open Directory Project (ODP) and Social Information Processing (SIP). Through catching of social information in conference website: i.e. the information of co-authorship or collaborator, research topics can be associated among related researchers. Finally, the experiments show Topic Maps successfully help researchers to find the information they need more easily and quickly as well as construct associations between research topics.

Keywords: knowledge management, topic map, social information processing, ontology extraction

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Authors: B. J. Kim, K. W. Nam, S. J. Lee

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Traditional social network services provide users with more information than is needed, and it is not easy to verify the authenticity of the information. This paper proposes a system that can only post messages where users are located to enhance the reliability of social networking services. The proposed system implements a Google Map API to post postings on the map and to read postings within a range of distances from the users’ location. The proposed system will only provide alerts, memories, and information about locations within a given range depending on the users' current location, providing reliable information that they believe will be necessary in real time. It is expected that the proposed system will be able to meet the real demands of users and create a more reliable social network services environment.

Keywords: social network, location, reliability, posting

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Authors: Mbah Fidelix Njong, Sabi Emile Forkwa

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Social cognition is an aspect of social psychology that focuses on how people process, store and apply information about others and social situations. It lay emphasis on how cognitive processes play in our social interactions. In this article, we try to show how culture can influence our ways of thinking about others, how we feel and interact with the world around us. Social cognitive processes involve perceiving people and how we learn about the people around us. It concerns the mental processes of remembering, thinking and attending to other people with different cultural backgrounds and how we attend to certain information about the world. Especially in an educational setting, students’ learning processes are most often than not influenced by their cultural background. We can also talk of social schemas. That’s people’s mental representation of social patterns and norms. This involves information about the societal role and the expectations of individuals within a group. These cognitive processes can also be influence by culture. There are important cultural differences in social cognition. In any social situation, two individuals may have different interpretations. Each person brings in a unique background of experiences, knowledge, social influence, feelings and cultural variations. Cultural differences can also affect how people interpret social situations. The same social behavior in one cultural setting might have completely different meaning and interpretation if observed or applied in another culture. However, as people interpret behaviors and bring out meaning from the interpretations, they act based on their beliefs about situations they are confronted with. This helps to reinforce and reproduce the cultural norms that influence their social cognition.

Keywords: social cognition, social schema, cultural influence, psychology

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Authors: R. Manjula, Kaustav Bagchi, Sushant Ramesh, Anush Baskaran

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In the past century, the emergence of information technology has had a significant positive impact on human life. While companies tend to be more involved in the completion of projects, the turn of the century has seen importance being given to investment in information security policies. These policies are essential to protect important data from adversaries, and thus following these policies has become one of the most important attributes revolving around information security models. In this research, we have focussed on the factors affecting information security policy compliance in two models : The theory of planned behaviour and the integration of the social bond theory and the involvement theory into a single model. Finally, we have given a proposal of where these theories would be successful.

Keywords: information technology, information security, involvement theory, policies, social bond theory

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Authors: Essam Mansour

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This study purposes to explore the adoption and use of social media as a source of information by Egyptian government journalists. It applied a survey with a total of 386 journalists representing the three official newspapers of Egypt. Findings showed that 27.2% of journalists were found to not use social media, mainly males (69.7%), older than 40 years (77.7%) and mostly with a BA degree (80.4%). On the other hand, 72.8% of them were found to use these platforms who were also males (59.1%), younger than 40 years (65.9%) and mostly with a BA degree (93.2%). More than two-thirds (69.9%) were somewhat old users whose experience ranged from seven to ten years, and more than two-thirds (73.5%) have been heavily using these platforms (four to more than six hours a day. Such results confirm that a large number (95.7%) of users were found to be at least advanced users. Social media users’ home and work were the most significant places to access these platforms, which were found to be easy and useful to use. Most types of social media used were social news, media sharing and micro blogging, blogs comments and forums, social networking sites and bookmarking sites to perform tasks, such as finding information, making communication, keeping up to date, checking materials, sharing information and making discussions. A large number of users tend to accept these media platforms to be a source of information since they are accessible, linked references updated sources, accurate, promote current work, convenient, secured, credible, reliable, stabled, easily identified, copyrighted, build confident and contain filtered information. However, lack of know-how to cite sources, followed by lack of credibility of the source of news, lack of quality of information sources and lack of time were at least significant to journalists when using social media platforms.

Keywords: social media, social networking sites, newspapers, journalists, Egypt

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Authors: Marion Billard

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This paper will focus on the question of the real relationship between young people and fake news. Fake news is one of today’s main issues in the world of information and communication. Social media and its democratization helped to spread false information. According to traditional beliefs, young people are more inclined to believe what they read through social media. But, the individuals concerned, think that they are more inclined to make a distinction between real and fake news. This phenomenon is due to their use of the internet and social media from an early age. During the 2016 and 2017 French and American presidential campaigns, the term fake news was in the mouth of the entire world and became a real issue in the field of information. While young people were informing themselves with newspapers or television until the beginning of the ’90s, Gen Z (meaning people born between 1997 and 2010), has always been immersed in this world of fast communication. They know how to use social media from a young age and the internet has no secret for them. Today, despite the sporadic use of traditional media, young people tend to turn to their smartphones and social networks such as Instagram or Twitter to stay abreast of the latest news. The growth of social media information led to an “ambient journalism”, giving access to an endless quantity of information. Waking up in the morning, young people will see little posts with short texts supplying the essential of the news, without, for the most, many details. As a result, impressionable people are not able to do a distinction between real media, and “junk news” or Fake News. This massive use of social media is probably explained by the inability of the youngsters to find connections between the communication of the traditional media and what they are living. The question arises if this over-confidence of the young people in their ability to distinguish between accurate and fake news would not make it more difficult for them to examine critically the information. Their relationship with media and fake news is more complex than popular opinion. Today’s young people are not the master in the quest for information, nor inherently the most impressionable public on social media.

Keywords: fake news, youngsters, social media, information, generation

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Authors: Niyi Awofeso, Yunes Gaber, Moyosola Bamidele

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Since most social media platforms are accessible anytime and anywhere where Internet connections and smartphones are available, the invisibility of the reader raises questions about accuracy, appropriateness and comprehensibility of social media communication. Furthermore, the identity and motives of individuals and organizations who post articles on social media sites are not always transparent. In the health sector, through socially networked platforms constitute a common source of health-related information, given their purported wealth of information. Nevertheless, fake blogs and sponsored postings for marketing 'natural cures' pervade most commonly used social media platforms, thus complicating readers’ abilities to access and understand trustworthy health-related information. This purposive sampling study of 120 participants aged 18-35 year in UAE was conducted between September and December 2017, and explored commonly used social media platforms, frequency of use of social media for accessing health related information, and approaches for assessing the trustworthiness of health information on social media platforms. Results indicate that WhatsApp (95%), Instagram (87%) and Youtube (82%) were the most commonly used social media platforms among respondents. Majority of respondents (81%) indicated that they regularly access social media to get health-associated information. More than half of respondents (55%) with non-chronic health status relied on unsolicited messages to obtain health-related information. Doctors’ health blogs (21%) and social media sites of international healthcare organizations (20%) constitute the most trusted source of health information among respondents, with UAE government health agencies’ social media accounts trusted by 15% of respondents. Cardiovascular diseases, diabetes, and hypertension were the most commonly searched topics on social media (29%), followed by nutrition (20%) and skin care (16%). Majority of respondents (41%) rely on reliability of hits on Google search engines, 22% check for health information only from 'reliable' social media sites, while 8% utilize 'logic' to ascertain reliability of health information. As social media has rapidly become an integral part of the health landscape, it is important that health care policy makers, healthcare providers and social media companies collaborate to promote the positive aspects of social media for young people, whilst mitigating the potential negatives. Utilizing popular social media platforms for posting reader-friendly health information will achieve high coverage. Improving youth digital literacy will facilitate easier access to trustworthy information on the internet.

Keywords: social media, United Arab Emirates, youth engagement, digital literacy

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Authors: Pekka Makkonen, Georgios Lampropoulos, Kerstin Siakas

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This paper examines the impact of social media on knowledge work. It discloses and highlights which specific aspects, areas and tasks of knowledge work can be improved by the use of social media. Moreover, the study includes a survey about higher education students’ viewpoints in regard to the use of social media as a means to enhance knowledge work and knowledge sharing. The analysis has been conducted based both on empirical data and on discussions about the sources dealing with knowledge work and how it can be enhanced by using social media. The results show that social media can improve knowledge work, knowledge building and maintenance tasks in which communication, information sharing and collaboration play a vital role. Additionally, by using social media, personal, collaborative and supplementary work activities can be enhanced. Based on the results of the study, we suggest how knowledge work can be enhanced when using the contemporary information and communications technologies (ICTs) of the 21^st century and recommend future directions towards improving knowledge work.

Keywords: knowledge work, social media, social media services, improving work performance

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Authors: Aria Teimourzadeh, Marc Favier, Samaneh Kakavand

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The emergence of social networks has revolutionized the exchange of information. Every behavior on these platforms contributes to the generation of data known as social network data that are processed, stored and published by the social network service providers. Hence, it is vital to investigate the role of these platforms in user data by considering the privacy measures, especially when we observe the increased number of individuals and organizations engaging with the current virtual platforms without being aware that the data related to their positioning, connections and behavior is uncovered and used by third parties. Performing analytics on social network datasets may result in the disclosure of confidential information about the individuals or organizations which are the members of these virtual environments. Analyzing separate datasets can reveal private information about relationships, interests and more, especially when the datasets are analyzed jointly. Intentional breaches of privacy is the result of such analysis. Addressing these privacy concerns requires an understanding of the nature of data being accumulated and relevant data privacy regulations, as well as motivations for disclosure of personal information on social network platforms. Some significant points about how user's online information is controlled by the influence of social factors and to what extent the users are concerned about future use of their personal information by the organizations, are highlighted in this paper. Firstly, this research presents a short literature review about the structure of a network and concept of privacy in Online Social Networks. Secondly, the factors of user behavior related to privacy protection and self-disclosure on these virtual communities are presented. In other words, we seek to demonstrates the impact of identified variables on user information disclosure that could be taken into account to explain the privacy preservation of individuals on social networking platforms. Thirdly, a few research directions are discussed to address this topic for new researchers.

Keywords: information disclosure, privacy measures, privacy preservation, social network analysis, user experience

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Authors: Francesco Buccafurri, Celeste Romolo

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Nowadays phishing is the most frequent starting point of cyber-attack vectors. Phishing is implemented both via email and social network messages. While a wide scientific literature exists which addresses the problem of contrasting email spam-phishing, no specific countermeasure has been so far proposed for phishing included into private messages of social network platforms. Unfortunately, the problem is severe. This paper proposes an approach against social network phishing, based on a non invasive collaborative information-sharing approach which leverages blockchain. The detection method works by filtering candidate messages, by distilling them by means of a distance-preserving hash function, and by publishing hashes over a public blockchain through a trusted smart contract (thus avoiding denial of service attacks). Phishing detection exploits social information embedded into social network profiles to identify similar messages belonging to disjoint contexts. The main contribution of the paper is to introduce a new approach to contrasting the problem of social network phishing, which, despite its severity, received little attention by both research and industry.

Keywords: phishing, social networks, information sharing, blockchain

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Authors: Kanda Runapongsa Saikaew, Chaluemwut Noyunsan

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Nowadays social media information, such as news, links, images, or VDOs, is shared extensively. However, the effectiveness of disseminating information through social media lacks in quality: less fact checking, more biases, and several rumors. Many researchers have investigated about credibility on Twitter, but there is no the research report about credibility information on Facebook. This paper proposes features for measuring credibility on Facebook information. We developed the system for credibility on Facebook. First, we have developed FB credibility evaluator for measuring credibility of each post by manual human’s labelling. We then collected the training data for creating a model using Support Vector Machine (SVM). Secondly, we developed a chrome extension of FB credibility for Facebook users to evaluate the credibility of each post. Based on the usage analysis of our FB credibility chrome extension, about 81% of users’ responses agree with suggested credibility automatically computed by the proposed system.

Keywords: facebook, social media, credibility measurement, internet

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Authors: Kyoung-Jae Kim

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Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

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Authors: Jiyoung Lee, Andrew D. Gershoff, Jerry Jisang Han

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Most extant research on consumer privacy concerns and their willingness to share personal data has focused on contextual factors (e.g., types of information collected, type of compensation) that lead to consumers’ personal information disclosure. Unfortunately, the literature lacks a clear understanding of how consumers’ incidental psychological needs may influence consumers’ decisions to share their personal information with companies or brands. In this research, we investigate how social exclusion, which is an increasing societal problem, especially since the onset of the COVID-19 pandemic, leads to increased information disclosure intentions for consumers. Specifically, we propose and find that when consumers become socially excluded, their desire for social connection increases, and this desire leads to a greater willingness to disclose their personal information with firms. The motivation to form and maintain interpersonal relationships is one of the most fundamental human needs, and many researchers have found that deprivation of belongingness has negative consequences. Given the negative effects of social exclusion and the universal need to affiliate with others, people respond to exclusion with a motivation for social reconnection, resulting in various cognitive and behavioral consequences, such as paying greater attention to social cues and conforming to others. Here, we propose personal information disclosure as another form of behavior that can satisfy such social connection needs. As self-disclosure can serve as a strategic tool in creating and developing social relationships, those who have been socially excluded and thus have greater social connection desires may be more willing to engage in self-disclosure behavior to satisfy such needs. We conducted four experiments to test how feelings of social exclusion can influence the extent to which consumers share their personal information with brands. Various manipulations and measures were used to demonstrate the robustness of our effects. Through the four studies, we confirmed that (1) consumers who have been socially excluded show greater willingness to share their personal information with brands and that (2) such an effect is driven by the excluded individuals’ desire for social connection. Our findings shed light on how the desire for social connection arising from exclusion influences consumers’ decisions to disclose their personal information to brands. We contribute to the consumer disclosure literature by uncovering a psychological need that influences consumers’ disclosure behavior. We also extend the social exclusion literature by demonstrating that exclusion influences not only consumers’ choice of products but also their decision to disclose personal information to brands.

Keywords: consumer-brand relationship, consumer information disclosure, consumer privacy, social exclusion

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Authors: Pui-Lai To, Chechen Liao, Tzu-Ling Lin

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Virtual communities have created a range of new social spaces in which to meet and interact with one another. Both as a stand-alone model or as a supplement to sustain competitive advantage for normal business models, building virtual communities has been hailed as one of the major strategic innovations of the new economy. However for a virtual community to evolve, the biggest challenge is how to make members actively give information or provide advice. Even in busy virtual communities, usually, only a small fraction of members post information actively. In order to investigate the determinants of information giving willingness of those contributors who usually actively provide their opinions, we proposed a model to understand the reasons for contribution in communities. The study will definitely serve as a basis for the future growth of information giving in virtual communities.

Keywords: information giving, social identity, trust, virtual community

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Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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Authors: Utkrash Sarkar, Vineet Tiwari, Shailendra Singh

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The development of social media has brought about a tremendous change in the marketing scenario for every industry. It has become a new hybrid element of the promotional mix in the marketing segment. This paper tries to show some light on the fact that in today’s scenario social media is a platform that everyone should take in consideration for any type of marketing campaign. In this paper, we have formulated a questionnaire, and through it, we have tried to gather information from the respondents that how social media is influencing their decision when they choose their travel destinations for tourism purpose, does it help in creating any awareness about places which they don’t have an idea? As a result, guiding the state government and providing them with a marketing strategy that how they can use social media in a better manner so that they could help increase their revenue and can make people aware about the places of the state which the target audience can plan to go for their next vacation.

Keywords: social media, marketing, information, decision making

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Authors: Zineb Meniaoui, Fatma Zehri, Kamoussi Halioui

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The amplified awareness of companies towards the social and environmental concerns has nowadays become a challenge for firms around the globe. Our study investigates the effects of corporate governance mechanisms on voluntarily social and environmental information disclosure in Canada and France. The study use the content analysis approach, applied on a total of 245 year-observation for the Canadian sample and 245 year-observation for the French sample from 2005 to 2011. Our results show a significant correlation between the board's independence, Corporate Social Responsibility (CSR) committee and expertise as well as the audit quality along with the extent of the social and environmental disclosure. The French firms are found disclosing more societal information than Canadian firms, which might be due to the stakeholders' pressure put on French companies to disclose such societal information.

Keywords: Canada, corporate governance, disclosure determinants , France, social and environmental disclosure

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Authors: Ly Thi Hai Yen

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The Internet in Vietnam has developed significantly over the last 20 years and made impressive advances, permeating into every part of daily life, changing people's habits as well as the way people's communication. Under this situation, social media have become useful tools for the citizen to get and share information. About 10 years ago, most Vietnamese people got the information through state media, but thanks to the development of the Internet, nowadays, social media have been giving them rich sources of information at any area of society. By using case study research methods, documentary research method and in-depth interviews conducted with social media users, NGO activists, and Vietnamese scholars in 2017, the paper found that social media has been bringing a cyber public sphere to whom wish to discuss social and political issues. And, more importantly, it gives them a chance to connect with the government and policy makers quickly and effectively. Moreover, people use social media to supervise activities in society to prevent social evils and corruption in Vietnam. However, besides these positive points, people also have to cope with the rising situation of fake news which causing consequences for the society, such as pulling off crimes or cheating money and others. The paper concluded that social media plays important roles in the change of Vietnamese society, giving citizens a cyber public sphere unrestrictedly to discuss social and political issues but also bringing many bad risks to citizens.

Keywords: Vietnamese, social media, politics-society

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Authors: Gabriel Gomez

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The very concept of information seeking behavior, and the means by which librarians teach users to gain information, that is information literacy, are at the heart of how libraries deliver information, but big data will forever change human interaction with information and the way such behavior is both studied and taught. Just as importantly, big data will orient the study of behavior towards commercial ends because of a tendency towards instrumentalist views of human behavior, something one might also call a trend towards behaviorism. This oral presentation seeks to explore how the impact of big data on understandings of human behavior might impact a library information science (LIS) view of human behavior and information literacy, and what this might mean for social justice aims and concomitant community action normally at the center of librarianship. The methodology employed here is a non-empirical examination of current understandings of LIS in regards to social justice alongside an examination of the benefits and dangers foreseen with the growth of big data analysis. The rise of big data within the ever-changing information environment encapsulates a shift to a more mechanistic view of human behavior, one that can easily encompass information seeking behavior and information use. As commercial aims displace the important political and ethical aims that are often central to the missions espoused by libraries and the social sciences, the very altruism and power relations found in LIS are at risk. In this oral presentation, an examination of the social justice impulses of librarians regarding power and information demonstrates how such impulses can be challenged by big data, particularly as librarians understand user behavior and promote information literacy. The creeping behaviorist impulse inherent in the emphasis big data places on specific solutions, that is answers to question that ask how, as opposed to larger questions that hint at an understanding of why people learn or use information threaten library information science ideals. Together with the commercial nature of most big data, this existential threat can harm the social justice nature of librarianship.

Keywords: big data, library information science, behaviorism, librarianship

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Authors: Yassine Jamoussi, Ameni Youssfi, Henda Ben Ghezala

Abstract:

With the growing interest in social networking, the interaction of social actors evolved to a source of knowledge in which it becomes possible to perform context aware-reasoning. The information extraction from social networking especially Twitter and Facebook is one of the problems in this area. To extract text from social networking, we need several lexical features and large scale word clustering. We attempt to expand existing tokenizer and to develop our own tagger in order to support the incorrect words currently in existence in Facebook and Twitter. Our goal in this work is to benefit from the lexical features developed for Twitter and online conversational text in previous works, and to develop an extraction model for constructing a huge knowledge based on actions

Keywords: social networking, information extraction, part-of-speech tagging, natural language processing

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Authors: Gaye Ibrahima, Mendy Gervais, Seck Diaraf, Ouya Samuel

Abstract:

In this paper, we consider the influence maximization in social networks. Here we give importance to initial diffuser called the seeds. The goal is to find efficiently a subset of k elements in the social network that will begin and maximize the information diffusion process. A new approach which treats the social network before to determine the seeds, is proposed. This treatment eliminates the information feedback toward a considered element as seed by extracting an acyclic spanning social network. At first, we propose two algorithm versions called SCG − algoritm (v1 and v2) (Spanning Connected Graphalgorithm). This algorithm takes as input data a connected social network directed or no. And finally, a generalization of the SCG − algoritm is proposed. It is called SG − algoritm (Spanning Graph-algorithm) and takes as input data any graph. These two algorithms are effective and have each one a polynomial complexity. To show the pertinence of our approach, two seeds set are determined and those given by our approach give a better results. The performances of this approach are very perceptible through the simulation carried out by the R software and the igraph package.

Keywords: acyclic spanning graph, centrality measures, information feedback, influence maximization, social network

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