Infer user interests via link structure regularization

Learning user interests from online social networks helps to better understand user behaviors and provides useful guidance to design user-centric applications. Apart from analyzing users' online content, it is also important to consider users' social connections in the social Web. Graph regularization methods have been widely used in various text mining tasks, which can leverage the graph structure information extracted from data. Previously, graph regularization methods operate under the cluster assumption that nearby nodes are more similar and nodes on the same structure (typically referred to as a cluster or a manifold) are likely to be similar. We argue that learning user interests from complex, sparse, and dynamic social networks should be based on the link structure assumption under which node similarities are evaluated based on the local link structures instead of explicit links between two nodes. We propose a regularization framework based on the relation bipartite graph, which can be constructed from any type of relations. Using Twitter as our case study, we evaluate our proposed framework from social networks built from retweet relations. Both quantitative and qualitative experiments show that our proposed method outperforms a few competitive baselines in learning user interests over a set of predefined topics. It also gives superior results compared to the baselines on retweet prediction and topical authority identification

Exploring Users’ Interactive Behaviors in Online Group: A Case Study of QQ Group “TuanRenTang”

The users’ interactive behaviors of the online group chat and an accurate identification of users’ interaction, which can provide method support for mining user interests and the crowd labeling, was analyzed in this paper. By using social network analysis method, the study took QQ Group “TuanRenTang” as an example to analyze users’ interactive behaviors, discover users’ interaction relationships, construct interaction networks, and explore the interaction types and community detection. The findings suggested that both explicit and implicit interaction exist in the same topic discussion. Users could be classified into four categories: active interaction, general interaction, passive interaction and lurking interaction based on different user activity. Besides, twenty “experts” and eight communities on the basis of interaction networks had been found out from the sample data of “TuanRenTang” chat records

Understanding the user display names across social networks

The display names that an individual uses in various online social networks always contain some redundant information because some people tend to use the similar names across different networks to make them easier to remember or to build their online reputation. In this paper, we aim to measure the redundant information between different display names of the same individual. Based on the cross-site linking function, we first develop a specific distributed crawler to extract the display names that individuals select for different social networks, and we give an overview on the display names we extracted. Then we measure and analyze the redundant information in three ways: length similarity, character similarity and letter distribution similarity, comparing with display names of different individuals. We also analyze the evolution of redundant information over time. We find 45% of users tend to use the same display name across OSNs. Our findings also demonstrate that display names of the same individual show high similarity. The evolution analysis results show that redundant information is time-independent. Awareness of the redundant information between the display names can benefit many applications, such as user identification across social networks

Secure Identification in Social Wireless Networks

The applications based on social networking have brought revolution towards social life and are continuously gaining popularity among the Internet users. Due to the advanced computational resources offered by the innovative hardware and nominal subscriber charges of network operators, most of the online social networks are transforming into the mobile domain by offering exciting applications and games exclusively designed for users on the go. Moreover, the mobile devices are considered more personal as compared to their desktop rivals, so there is a tendency among the mobile users to store sensitive data like contacts, passwords, bank account details, updated calendar entries with key dates and personal notes on their devices. The Project Social Wireless Network Secure Identification (SWIN) is carried out at Swedish Institute of Computer Science (SICS) to explore the practicality of providing the secure mobile social networking portal with advanced security features to tackle potential security threats by extending the existing methods with more innovative security technologies. In addition to the extensive background study and the determination of marketable use-cases with their corresponding security requirements, this thesis proposes a secure identification design to satisfy the security dimensions for both online and offline peers. We have implemented an initial prototype using PHP Socket and OpenSSL library to simulate the secure identification procedure based on the proposed design. The design is in compliance with 3GPP‟s Generic Authentication Architecture (GAA) and our implementation has demonstrated the flexibility of the solution to be applied independently for the applications requiring secure identification. Finally, the thesis provides strong foundation for the advanced implementation on mobile platform in future

Jointly they edit: examining the impact of community identification on political interaction in Wikipedia

In their 2005 study, Adamic and Glance coined the memorable phrase "divided they blog", referring to a trend of cyberbalkanization in the political blogosphere, with liberal and conservative blogs tending to link to other blogs with a similar political slant, and not to one another. As political discussion and activity increasingly moves online, the power of framing political discourses is shifting from mass media to social media. Continued examination of political interactions online is critical, and we extend this line of research by examining the activities of political users within the Wikipedia community. First, we examined how users in Wikipedia choose to display (or not to display) their political affiliation. Next, we more closely examined the patterns of cross-party interaction and community participation among those users proclaiming a political affiliation. In contrast to previous analyses of other social media, we did not find strong trends indicating a preference to interact with members of the same political party within the Wikipedia community. Our results indicate that users who proclaim their political affiliation within the community tend to proclaim their identity as a "Wikipedian" even more loudly. It seems that the shared identity of "being Wikipedian" may be strong enough to triumph over other potentially divisive facets of personal identity, such as political affiliation.Comment: 33 pages, 5 figure

Secure Mobile Social Networks using USIM in a Closed Environment

Online social networking and corresponding mobile based applications are gaining popularity and now considered a well-integrated service within mobile devices. Basic security mechanisms normally based on passwords for the authentication of social-network users are widely deployed and poses a threat for the user security. In particular, for dedicated social groups with high confidentiality and privacy demands, stronger and user friendly principles for the authentication and identification of group members are needed. On the other hand, most of the mobile units already provide strong authentication procedures through the USIM/ISIM module. This paper explores how to build an architectural framework for secure enrollment and identification of group members in dedicated closed social groups using the USIM/SIM authentication and in particular, the 3GPP Generic Authentication Architecture (GAA), which is built upon the USIM/SIM capabilities. One part of the research is to identify the marketable use-cases with corresponding security challenges to fulfill the requirements that extend beyond the online connectivity. This paper proposes a secure identification design to satisfy the security dimensions for both online and offline peers. We have also implemented an initial proof of the concept prototype to simulate the secure identification procedure based on the proposed design. Our implementation has demonstrated the flexibility of the solution to be applied independently for applications requiring secure identification