A Comparison of Intercultural Student Communities in Online Social Networks

Abstract This work is geared to analyze informal learning processes in student conferences. In particular, it compares social network interactions occurring in conference-related Facebook pages - i. e. Taiwan-America Student Conference (TASC), Japan-America Student Conference (JASC) and Korea-America Student Conference (KASC) pages - within a period starting 30 days before and finishing 30 days after the application deadlines. This empirical study has been realized by adopting open source visualization tools and techniques freely available on the software market in order to perform Social Network Analysis (SNA) in a transparent and reproducible way. Such an analysis provides interesting information on interaction dynamics, emerging hot topics and sub-group formation of attending students

analyzing informal learning patterns in facebook communities of international conferences

Abstract This paper is geared to analyze learning interactions between members of Facebook communities. In particular, this study considers the online dynamics occurring in academic communities associated with international conferences. The data collection process covers 40 days of pre-event activities within the conference-related Facebook community, and aims at elaborating and interpreting such data in order to provide useful information on how to create an online breeding environment for such international events

Detecting Tie Strength from Social Media Data in a Conference Setting

The concept of tie strength was introduced by Granovetter as “a (probably linear) combination of the amount of time, the emotional intensity, the intimacy (mutual confiding), and the reciprocal services which characterize the tie”. Since the publication of this seminal study, several studies have been conducted incorporating the concept of tie strength in numerous fields. The growing rise of social media in recent years has shaped a new way of establishing and maintaining ties between people. As a result, studies have been conducted that, based on social media data, are focused on the evaluation of tie strength between users. Social media has also positioned itself as a key tool in the development of events such as conferences, as it is consolidated as the communication platform through which to disseminate information and knowledge and networking. Therefore, in the present study, it is sought to evaluate tie strength using publicly available Twitter data in the context of a conference. Specifically, the aim is to analyse the potential of implicit networks (particularly, mentions networks) generated in social media sites (particularly, Twitter) when evaluating tie strength and social ties, with special emphasis on weak ties and latent ties. Ultimately, the aim is to obtain conclusions that result in the demonstration of the utility and the advantages of implementing this analysis in the recommendation systems in conferences. To address the main statement problem, this study starts with a review of the existing literature related to the topic. Subsequently, as regards the empirical part of the study, a case study approach is conducted. Specifically, a longitudinal single-case analysis is analysed, since the mentions networks generated from the publicly available Twitter data of the conference HICSS along nine editions (from 2010 to 2018) are studied. Different measures of social network analysis have been used to obtain results and conclusions. Based on the analysis, different potentially useful measures for the evaluation of mentions networks and social ties are identified. These measures have served to analyse the social structures formed in a conference setting (highlighting star structures that reflect the information disseminating role of certain nodes), to identify the most relevant and influential participants (which generally correspond to important roles of the conference, as organizers or speakers), or to observe tendencies and groupings in communities according to common interests, among others

Evaluating tie strength from Twitter data in conference setting: Case CMAD

The concept of tie strength as well as the different kind of ties- strong and weak ties was introduced by Granovetter in his seminal paper titled “Strength of Weak Ties”. Over the decades, this concept has been used in a variety of fields to study a lot of different phenomena. In the recent years, the rise of social media and social networking services has given rise to new ways of maintaining and establishing ties. This has resulted in studies that have used personal social media data to predict the tie strength of these online relationships. Social media is also being used in events like conferences for networking purposes. In this study we evaluate the tie strength and identify different kind of ties using publically available Twitter data in the context setting of a conference. In order to address the formulated research problem, this study began by reviewing the relevant literature related to tie strength, social media and conference setting. From the literature review it was observed that: communication frequency was the most commonly used proxy for tie strength evaluation; social media was used for networking in conferences; and current methods of tie strength evaluation from social media use personal social media data which may not be accessible in case of conferences. The empirical study used the single-case based case of CMAD which is community managers’ online discussions in social media in connection to yearly-organized Community Manager Appreciation Day event in Finland. Two different data sources (survey data and Twitter data) were used to carry out the analysis. Different social network analysis methods were used to analyze the case. Based on the analysis, it was possible to identify potentially useful dimensions (e.g. amount of time, reciprocal services and structural factors) and measures (e.g. weighted degree, shortest path length) for evaluating tie strength in the context of events. These measures were useful in identifying to a useful extent the strong ties and the potential weak ties in the context of this study

Information visualization of Twitter data for co-organizing conferences

The aim of this research is to explore what kinds of insights information visualization of social media data can provide for co-organizing conferences. Our paper focuses on Twitter in ‘during-conference’ use. We present a case study based on CMAD2013 conference and on the tweet traffic during the conference day. We applied the process of data-driven visual network analysis for providing insights on Twitter use during CMAD2013 conference day. By analyzing the network of conference participants and the conference’s discussion topics, we were able to identify e.g. influential conference delegates, most interesting presentations and discussions, similarities between interests of the conference participants, and several development and information needs of conference co-organization derived from the information visualizations, which have implications for the planning and co-organizing of conferences, as well as for Twitter use in communicating during conferences.Peer reviewe

The Impact of Community Cohesion on Crime

Community cohesion generally acts to increase the safety of communities by increasing informal guardianship, and enhancing the work of formal crime prevention organisations. Understanding the dynamics of local social interactions is essential for community building. However, community cohesion is difficult to empirically quantify, because there are no obvious and direct indicators of community cohesion collected at population levels within official datasets. A potentially more promising alternative for estimating community cohesion is through the use of data from social media. Social media offers an opportunity for exploring networks of social interactions in a local community. This research will use social media data to explore the impact of community cohesion on crime. Sentiment analysis of tweets can help to uncover patterns of community mood in different areas. Modelling of community engagement on Facebook is useful for understanding patterns of social interactions and the strength of social networks in local communities. The central contribution of this thesis is the use of new metrics that estimate popularity, commitment and virality known as the PCV indicators for quantifying community cohesion on social media. These metrics, combined with diversity statistics constructed from “traditional” Census data, provide a better correlate of community cohesion and crime. To demonstrate the viability of this novel method for estimating the impact of community cohesion, a model of community engagement and burglary rates is constructed using Leeds community areas as an example. By examining the diversity of different community areas and strength of their social networks, from traditional and new data sources; it was found that stability and strong social media engagement in a local area are associated with lower burglary rates. The proposed new method can provide a better alternative for estimating community cohesion and its impact on crime. It is recommended that policy planning for resource allocation and community building needs to consider social structure and social networks in different communities