Analyzing microblogs with affinity propagation

Recently, there has been a great deal of interest in analyz-ing inherent structures in posts on microblogs such as Twit-ter. While many works utilize a well-known topic modeling technique, we instead propose to apply Affinity Propaga-tion [4] (AP) to analyze such a corpus, and we hypothesize that AP may provide different perspective to the traditional approach. Our preliminary analysis raises some interesting facts and issues, which suggest future research directions

A Net Loan Monitoring Platform for University Students Based on Visual Micro-blog

In order to prevent college students from tragic events, which mostly result from falling into illegal net loan, a net loan risk monitoring platform of college students was established based on the microblog visualization. Based on the calculation model of risk degree (CMRD) and the calculation model of relational closeness (CMRC), a visual system, a user relationship analysis system and an early warning system were constructed on the platform. Through the CMRD, the risk degree of micro-blog net loan contents can be worked out to decide whether warning behaviors are necessary. Through the CMRC, the closeness of net loan bloggers with users can be obtained a propagation map. The key nodes can be cut off by internet security officers in time, which can prevent further propagation of the contents of the microblog net loan. The platform can effectively alleviate the tense situation of college students and illegal online loans

Effectiveness of Corporate Social Media Activities to Increase Relational Outcomes

This study applies social media analytics to investigate the impact of different corporate social media activities on user word of mouth and attitudinal loyalty. We conduct a multilevel analysis of approximately 5 million tweets regarding the main Twitter accounts of 28 large global companies. We empirically identify different social media activities in terms of social media management strategies (using social media management tools or the web-frontend client), account types (broadcasting or receiving information), and communicative approaches (conversational or disseminative). We find positive effects of social media management tools, broadcasting accounts, and conversational communication on public perception

Finding influential users of web event in social media

Users of social media have different influences on the evolution of a Web event. Finding influential users could benefit such information services as recommendation and market analysis. However, most of the existing methods are only based on social networks of users or user behaviors while the role of the contents contributed by users in social media is ignored. In fact, a Web event evolves with both user behaviors and the contents. This paper proposes an approach to find influential users by extracting user behavior network and association network of words within the contents and then uses PageRank algorithm and HITS algorithm to calculate the influence of users on the integration of two networks. The proposed approach is effective on several real-world datasets