在线社交网络中的位置服务研究进展与趋势

在基于位置的社交网络中, 用户通过发布嵌入了位置数据的媒体信息获得服务, 如位置或好友推荐、旅行路线推荐等。用户和位置都是网络的主体, 位置作为桥梁将用户的虚拟网络世界与现实世界联系起来。综述了基于位置的在线社交网络中的位置信息获取、用户识别、位置识别、信息的共享与传播及位置隐私的相关研究, 预测了基于位置的在线社交网络未来的研究趋势。     

Birds of a feather locate together? Foursquare checkins and personality homophily

In this paper we consider whether people with similar personality traits have a preference for common locations. Due to the difficulty in tracking and categorising the places that individuals choose to visit, this is largely unexplored. However, the recent popularity of location-based social networks (LBSNs) provides a means to gain new insight into this question through checkins - records that are made by LBSN users of their presence at specific street level locations. A web-based participatory survey was used to collect the personality traits and checkin behaviour of 174 anonymous users, who, through their common check-ins, formed a network with 5373 edges and an approximate edge density of 35%. We assess the degree of overlap in personality traits for users visiting common locations, as detected by user checkins. We find that people with similar high levels of conscientiousness, openness or agreeableness tended to have checked-in locations in common. The findings for extraverts were unexpected in that they did not provide evidence of individuals assorting at the same locations, contrary to predictions. Individuals high in neuroticism were in line with expectations, they did not tend to have locations in common. Unanticipated results concerning disagreeableness are of particular interest and suggest that different venue types and distinctive characteristics may act as attractors for people with particularly selective tendencies. These findings have important implications for decision-making and location.     

ComBiNet: Visual Query and Comparison of Bipartite Multivariate Dynamic Social Networks

We present ComBiNet, a visualization, query, and comparison system for exploring bipartite multivariate dynamic social networks. Historians and sociologists study social networks constructed from textual sources mentioning events related to people, such as marriage acts, birth certificates and contracts. We model this type of data using bipartite multivariate dynamic networks to maintain a representation faithful to the original sources while not too complex. Relying on this data model, ComBiNet allows exploring networks using both visual and textual queries using the Cypher language, the two being synchronized to specify queries using the most suitable modality; simple queries are easy to express visually and can be refined textually when they become complex. These queries are used for applying topological and attribute-based selection on the network. Query results are visualized in the context of the whole network and over a geographical map for geolocalized entities. We also present the design of our interaction techniques for querying social networks to visually compare the selections in terms of topology, measures and attribute distributions. We validate the query and comparison systems by showing how they have been used to answer historical questions and by explaining how they have been improved through a usability study conducted with historians.     

Collecting and Sharing Location-based Content on Mobile Phones in a Zoo Visitor Experience

The augmentation of visitor experiences with location-based technologies has been available for some time. Through in-depth studies of users during these experiences the field is building a rich picture of user behaviour in relation to certain location-based technologies. However, little work has explored the use of mobile camera phones and 2D barcodes on situated signs and their properties as a way of delivering such augmented visitor experiences. In this paper we present a study of people engaged in such a location-based experience at London zoo in which they use mobile camera phones to read 2D barcodes on signs at the animal enclosures in order to access related content. Through the fieldwork we highlight the social and collaborative aspects of the experience and how particular characteristics of the mobile phone and barcode technology shape these behaviours. The paper also highlights some of the non-instrumental aspects of the location-based experience, in particular in relation to the importance of collecting location-based content. We explore the social aspects of collecting as well as certain competitive elements it introduces into people’s behaviour. This creates an interesting tension in that aspects of the application encourage cooperation and sharing among the visitors whereas others encourage competition. In the course of presenting the fieldwork, we explore this tension further.     

How to keep members using the information in a computer-supported social network

Computer-supported social networks have become a significant channel for people to interact and exchange information. The success of computer-supported social networks depends on the extent to which members will stay and continue participating. Many computer-supported social networks however suffer from the problem of retaining members. Drawing from theories of user satisfaction and information adoption, we develop a model to examine how computer-supported social networks encourage members to continue participating and using the information in the network. The theoretical model is validated through an online survey of 240 users of a Bulletin Board System established by a local university in China. The results reveal that individuals will continue to use the information in a computer-supported social network when they are satisfied with their prior usage, and when they perceive that the information in the network is useful. The results also suggest that individuals’ perceived information usefulness and satisfaction are determined by information quality and source credibility in the context of computer-supported social networks. Theoretical and practical implications about computer-supported social networks are discussed.     

Fusing pattern discovery and visual analytics approaches in tweet propagation

Over the past several years, social networks have become a major channel for information delivery. At present, social networks are being used to obtain more followers and exert influence over people during political campaigns. However, the propagation of a social network post is dependent on numerous factors. Some of these are known; for example, the post contents, the time when it was posted, and the person or entity by whom it was posted. However, other factors remain unknown, such as what makes a post more successful than others, and how posts from similar profiles evolve and propagate differently over time. The main subject of this work is addressing these types of questions. Our approach relies on a three-fold methodology for studying the influence and propagation of posts: graph-based, semantic, and contrast pattern recognition analysis. The results obtained are complemented by a dynamic visualization that encompasses all of the variables involved. In order to corroborate our results, we collected all posts from the Twitter accounts of the most prominent Mexican political figures and analyzed the influence and propagation of each post issued.     

基于WebGIS的地理社交网络空间构建

现代社会电子社交的网络越大越大,基于WebGIS的地理社交网络服务也融入了人们的生活.地理社交网络推出了很多位置信息服务,受到平台框架与语言编写的限制,定位精度受到了很大的影响,而地理位置服务也大多停留于签到与信息分享层面上,并未真正实现空间位置服务.本文对我国网络地理信息系统结构和实现的技术进行研究,提出了基于WebGIS的地理社交网络构建,为人们的出行服务更顺畅服务,满足无网络离线状态的地图查询与应用.     

Like-minded communities: bringing the familiarity and similarity together

Community detection in social networks is a well-studied problem. A community in social network is commonly defined as a group of people whose interactions within the group are more than outside the group. It is believed that people’s behavior can be linked to the behavior of their social neighborhood. While shared characteristics of communities have been used to validate the communities found, to the best of authors’ knowledge, it is not demonstrated in the literature that communities found using social interaction data are like-minded, i.e., they behave similarly in terms of their interest in items (e.g., movie, products). In this paper, we experimentally demonstrate, on a social networking movie rating dataset, that people who are interested in an item are socially better connected than the overall graph. Motivated by this fact, we propose a method for finding communities wherein like-mindedness is an explicit objective. We find small tight groups with many shared interests using a frequent item set mining approach and use these as building blocks for the core of these like-minded communities. We show that these communities have higher similarity in their interests compared to communities found using only the interaction information. We also compare our method against a baseline where the weight of edges are defined based on similarity in interests between nodes and show that our approach achieves far higher level of like-mindedness amongst the communities compared to this baseline as well.     

Social networks applied

Social networks have interesting properties. They influence our lives enormously without us being aware of the implications they raise. The authors investigate the following areas concerning social networks: how to exploit our unprecedented wealth of data and how we can mine social networks for purposes such as marketing campaigns; social networks as a particular form of influence, i.e.., the way that people agree on terminology and this phenomenon's implications for the way we build ontologies and the Semantic Web; social networks as something we can discover from data; the use of social network information to offer a wealth of new applications such as better recommendations for restaurants, trustworthy email senders, or (maybe) blind dates; investigation of the richness and difficulty of harvesting FOAF (friend-of-a-friend) information; and by looking at how information processing is bound to social context, the resulting ways that network topology's definition determines its outcomes.     

Looking for the perfect tweet. The use of data mining techniques to find influencers on twitter

The purpose of this study is to investigate influencers on Twitter to discover the characteristics of their tweets through PIAR, a unique data mining research tool developed by the University of Salamanca that combines graph theory and social influence theory. An analysis of 3853 users posting about two automotive Japanese car firms, Toyota and Nissan, reveals the characteristics influencers have on this social network. The findings suggest that influencers use more hashtags and mentions on average when they tweet, and their word count is fewer than those with less power on this virtual community. Surprisingly, they tend to include less embedded links on their posts. Additionally, influencers have on average a large number of people they follow and they clearly express their opinions and feelings (either positive or negative) when tweeting. The results broaden the understanding of how influencers write and behave on social networks when they communicate with their users' community. Further, it provides insights for practitioners and marketers on how to discover influencers talking about their brands by observing tweets' content.     

More Network Conscious Than Ever? Challenges,Strategies, and Analytic Labor of Users in the Facebook Environment

As is widely observed, social network sites (SNS) constitute a new environment of interaction where users encounter various challenges that they usually do not encounter in other environments. This study aims to provide an in‐depth understanding of how users deal with the challenges in this unique environment, paying particular attention to the ways in which they examine and reflect on their social ties and networks. On the basis of 36 semistructured interviews with Facebook users, the article presents the hypothesis that participants of SNS develop a tendency to become highly observant and inquisitive about their networks and are frequently involved in an activity that the authors call analytic labor.     

“Newbies” and “Celebrities”: Detecting social roles in an online network of teachers via participation patterns

The advent of social networking tools allows teachers to create online networks and share information. While some virtual networks have a formal structure and defined boundaries, many do not. These unstructured virtual networks are difficult to study because they lack defined boundaries and a formal structure governing leadership roles and the transfer of information. The purpose of the study was to explore the relationship between how a member participates in a virtual blog network and the role of that member in the network. Unlike previous studies that use behavioral or structural characteristics of an individual’s network to infer social roles, this study utilized cluster analysis to combine behavior and structural information in role detection. Quantitative methods from social network analysis were used to compare the network structure of individual bloggers both across and within groups. The results indicate that how an individual participates in the network has an influence not only on their current role in the network, but also in how and how quickly their role in the community changes.     

IMing, Text Messaging, and Adolescent Social Networks

Building on previous research in computer-mediated communication, social and communication networks, and adolescent development, this article raises three issues regarding adolescent use of socially interactive technologies (SITs) and their relationship to offline social networks: 1) whether adolescents are creating more, but weaker ties using SITs, 2) to what extent adolescent SIT-facilitated networks overlap with friendship networks, and 3) whether SIT relationships are important for adolescents who have fewer offline peer ties. In order to investigate these questions, network data collection and analysis were integrated with more traditional questionnaire methodology and statistical analysis. The results show that the adolescents in the study were not creating more ties using SITs, nor were they necessarily creating weaker SIT-based ties; that there was little overlap between SIT-facilitated and offline social networks; and that socially isolated adolescents were less likely than other adolescents to use SITs.     

Analysis of MySpace user profiles

Online social networks have attracted millions of users, who have integrated social network web sites into their daily life. Users participate to the changes and to the evolution of these sites because they are producers and reviewers of contents that help them to maintain the existing social relationships, make new friends, collaborate and enrich experiences. This paper presents a study of the characteristics of the users of MySpace web site, with the objective of studying relationships and interactions among users and deriving hints about their behavior. The analysis relies on data collected by monitoring the web site for 12 weeks. Typical user behaviors have been derived and classes of users characterized by different levels of participation to the social network have been identified. In particular, the analysis reveals that most of the users actively participate to the social network and specify many personal details. Social networks web sites allow access to such details; the sharing of information about users and their relationships can lead to non-ethic online activities, which threat the privacy and the security of users themselves.     

Predictors of mobilizing online coping versus offline coping resources after negative life events

This exploratory study drew upon the social compensation/social enhancement hypotheses and weak tie network theory to predict what kind of people supplement offline coping resources with online coping resources more than others. Using a large, representative survey the authors found that low self-esteem, lonely, and socially isolated individuals add more online resources to their mix of preferred coping strategies than their counterparts. These groups benefit from the fact that online coping resources are not as strongly entangled with online social ties as are offline coping resources with offline ties, and from the fact that online coping resources can sometimes be mobilized without any social interactions. In contrast to offline coping, the researchers also found that men mobilize more online coping resources than women. The authors discuss the implications of these findings in terms of the social compensation hypothesis and online weak tie networks.     

Efficient techniques for time-constrained information dissemination using location-based social networks

Social networks have undergone an explosive growth in recent years. They constitute a central part of users׳ everyday lives as they are used as major tools for the spread of information, ideas and notifications among the members of the network. In this work we investigate the use of location-based social networks as a medium of emergency notification, for efficient dissemination of emergency information among members of the social network under time constraints. Our objective is the following: given a location-based social network comprising a number of mobile users, the social relationships among the users, the set of recipients, and the corresponding timeliness requirements, our goal is to select an appropriate subset of users so that the spread of information is maximized, time constraints are satisfied and costs are considered. We propose LATITuDE, our system that investigates the interactions among the members of the social network to infer their social relationships, and develop scalable dissemination mechanisms that select the most efficient set of users to initiate the dissemination process in order to maximize the information reach among the appropriate receivers within a time window. Our detailed experimental results illustrate that our approach is practical, effectively addresses the problem of informing the appropriate set of users within a deadline when an emergency event occurs, uses a small number of messages, and consistently outperforms its competitors.     

融合隐语义和邻域算法的兴趣点推荐模型*

近年来,随着众多具有传感功能的智能手机和可穿戴设备的普及,基于位置的服务得到了快速发展,其中基于位置的社交网络（location-based social networks,LBSN）逐渐被大多数人所接受,基于位置社交网络可以为人们提供兴趣点推荐服务,为了提供更加精准的兴趣点推荐服务本文提出了一种融合的算法模型。本文通过隐语义分析算法来充分挖掘用户的历史行为,使用基于邻域的方法结合好友和地理位置等因素,然后在统一的框架中融合这两种推荐方式的结果,实现了对用户行为更好的预测。实验结果表明,本文提出的兴趣点推荐方法拥有较好的准确率和召回率。     

irBlogs: A standard collection for studying Persian bloggers

A large number of internet users share their knowledge and opinions in online social networks like forums, weblogs, etc. This fact has attracted many researchers from different fields to study online social networks. The Persian language is one of the dominant languages in the Middle East which is the official language of Iran, Afghanistan and Tajikistan; so, a large number of Persians are active in online social networks. Despite this fact, very few studies exist about Persian social networks. In this paper we will study the characteristics of Persian bloggers based on a new collection, named irBlogs. The collection contains nearly 5 million posts and the network of more than 560,000 Persian bloggers which assures the reliability of the results of this study. Some of the analyzed characteristics are: the similarities and the differences between formal Persian and the language style that is used by Persian bloggers, the interests of the bloggers and the impact of other web resources on Persian blogosphere. Our analysis show that IT, sports, society, culture and politics are the main interests of Persian bloggers. Also, analysis of the links that are shared by Persian bloggers shows that news agencies, knowledge-bases and other social networks have a great impact on Persian bloggers and they are interested to share multimedia content.     

Gender Differences in Motivations for Identity Reconstruction on Social Network Sites

Social network sites provide people a unique opportunity for self-presentation. Due to various reasons, people may build an online identity that is partly or even completely different from their identity in the real world. Adopting social role theory as the theoretical foundation, the current study investigated gender differences in the motivations for virtual identity reconstruction on QQ, a social network site based in China. A total of 418 respondents participated in the study. As hypothesized, the results showed that men and women are motivated differently when reconstructing their identity – while women focus more on physical vanity, men emphasize achievement vanity. The authors also identified gender differences in other motivations for online identity reconstruction: bridging social capital, disinhibition, and privacy concerns. The results, which suggest that men and women behave in gender-specific ways, are in line with the propositions made in social role theory.