On the k-anonymization of time-varying and multi-layer social graphs

The popularity of online social media platforms provides an unprecedented opportunity to study real-world complex networks of interactions. However, releasing this data to researchers and the public comes at the cost of potentially exposing private and sensitive user information. It has been shown that a naive anonymization of a network by removing the identity of the nodes is not sufficient to preserve users’ privacy. In order to deal with malicious attacks, k -anonymity solutions have been proposed to partially obfuscate topological information that can be used to infer nodes’ identity. In this paper, we study the problem of ensuring k anonymity in time-varying graphs, i.e., graphs with a structure that changes over time, and multi-layer graphs, i.e., graphs with multiple types of links. More specifically, we examine the case in which the attacker has access to the degree of the nodes. The goal is to generate a new graph where, given the degree of a node in each (temporal) layer of the graph, such a node remains indistinguishable from other k-1 nodes in the graph. In order to achieve this, we find the optimal partitioning of the graph nodes such that the cost of anonymizing the degree information within each group is minimum. We show that this reduces to a special case of a Generalized Assignment Problem, and we propose a simple yet effective algorithm to solve it. Finally, we introduce an iterated linear programming approach to enforce the realizability of the anonymized degree sequences. The efficacy of the method is assessed through an extensive set of experiments on synthetic and real-world graphs.

Privacy and the City:user identification and location semantics in location-based social networks

With the advent of GPS enabled smartphones, an increasing number of users is actively sharing their location through a variety of applications and services. Along with the continuing growth of Location-Based Social Networks (LBSNs), security experts have increasingly warned the public of the dangers of exposing sensitive information such as personal location data. Most importantly, in addition to the geographical coordinates of the user’s location, LBSNs allow easy access to an additional set of characteristics of that location, such as the venue type or popularity. In this paper, we investigate the role of location semantics in the identification of LBSN users. We simulate a scenario in which the attacker’s goal is to reveal the identity of a set of LBSN users by observing their check-in activity. We then propose to answer the following question: what are the types of venues that a malicious user has to monitor to maximize the probability of success? Conversely, when should a user decide whether to make his/her check-in to a location public or not? We perform our study on more than 1 million check-ins distributed over 17 urban regions of the United States. Our analysis shows that different types of venues display different discriminative power in terms of user identity, with most of the venues in the “Residence” category providing the highest re-identification success across the urban regions. Interestingly, we also find that users with a high entropy of their check-ins distribution are not necessarily the hardest to identify, suggesting that it is the collective behaviour of the users’ population that determines the complexity of the identification task, rather than the individual behaviour.

Coding together at scale:GitHub as a collaborative social network

GitHub is the most popular repository for open source code (Finley 2011). It has more than 3.5 million users, as the company declared in April 2013, and more than 10 million repositories, as of December 2013. It has a publicly accessible API and, since March 2012, it also publishes a stream of all the events occurring on public projects. Interactions among GitHub users are of a complex nature and take place in different forms. Developers create and fork repositories, push code, approve code pushed by others, bookmark their favorite projects and follow other developers to keep track of their activities. In this paper we present a characterization of GitHub, as both a social network and a collaborative platform. To the best of our knowledge, this is the first quantitative study about the interactions happening on GitHub. We analyze the logs from the service over 18 months (between March 11, 2012 and September 11, 2013), describing 183.54 million events and we obtain information about 2.19 million users and 5.68 million repositories, both growing linearly in time. We show that the distributions of the number of contributors per project, watchers per project and followers per user show a power-law-like shape. We analyze social ties and repository-mediated collaboration patterns, and we observe a remarkably low level of reciprocity of the social connections. We also measure the activity of each user in terms of authored events and we observe that very active users do not necessarily have a large number of followers. Finally, we provide a geographic characterization of the centers of activity and we investigate how distance influences collaboration.

A question of complexity:measuring the maturity of online enquiry communities

Online enquiry communities such as Question Answering (Q&A) websites allow people to seek answers to all kind of questions. With the growing popularity of such platforms, it is important for community managers to constantly monitor the performance of their communities. Although different metrics have been proposed for tracking the evolution of such communities, maturity, the process in which communities become more topic proficient over time, has been largely ignored despite its potential to help in identifying robust communities. In this paper, we interpret community maturity as the proportion of complex questions in a community at a given time. We use the Server Fault (SF) community, a Question Answering (Q&A) community of system administrators, as our case study and perform analysis on question complexity, the level of expertise required to answer a question. We show that question complexity depends on both the length of involvement and the level of contributions of the users who post questions within their community. We extract features relating to askers, answerers, questions and answers, and analyse which features are strongly correlated with question complexity. Although our findings highlight the difficulty of automatically identifying question complexity, we found that complexity is more influenced by both the topical focus and the length of community involvement of askers. Following the identification of question complexity, we define a measure of maturity and analyse the evolution of different topical communities. Our results show that different topical communities show different maturity patterns. Some communities show a high maturity at the beginning while others exhibit slow maturity rate. Copyright 2013 ACM.

Mainstream media behavior analysis on Twitter:a case study on UK general election

With the development of social media tools such as Facebook and Twitter, mainstream media organizations including newspapers and TV media have played an active role in engaging with their audience and strengthening their influence on the recently emerged platforms. In this paper, we analyze the behavior of mainstream media on Twitter and study how they exert their influence to shape public opinion during the UK's 2010 General Election. We first propose an empirical measure to quantify mainstream media bias based on sentiment analysis and show that it correlates better with the actual political bias in the UK media than the pure quantitative measures based on media coverage of various political parties. We then compare the information diffusion patterns from different categories of sources. We found that while mainstream media is good at seeding prominent information cascades, its role in shaping public opinion is being challenged by journalists since tweets from them are more likely to be retweeted and they spread faster and have longer lifespan compared to tweets from mainstream media. Moreover, the political bias of the journalists is a good indicator of the actual election results. Copyright 2013 ACM.

Preface

The Semantic Web has come a long way since its inception in 2001, especially in terms of technical development and research progress. However, adoption by non- technical practitioners is still an ongoing process, and in some areas this process is just now starting. Emergency response is an area where reliability and timeliness of information and technologies is of essence. Therefore it is quite natural that more widespread adoption in this area has not been seen until now, when Semantic Web technologies are mature enough to support the high requirements of the application area. Nevertheless, to leverage the full potential of Semantic Web research results for this application area, there is need for an arena where practitioners and researchers can meet and exchange ideas and results. Our intention is for this workshop, and hopefully coming workshops in the same series, to be such an arena for discussion. The Extended Semantic Web Conference (ESWC - formerly the European Semantic Web conference) is one of the major research conferences in the Semantic Web field, whereas this is a suitable location for this workshop in order to discuss the application of Semantic Web technology to our specific area of applications. Hence, we chose to arrange our first SMILE workshop at ESWC 2013. However, this workshop does not focus solely on semantic technologies for emergency response, but rather Semantic Web technologies in combination with technologies and principles for what is sometimes called the "social web". Social media has already been used successfully in many cases, as a tool for supporting emergency response. The aim of this workshop is therefore to take this to the next level and answer questions like: "how can we make sense of, and furthermore make use of, all the data that is produced by different kinds of social media platforms in an emergency situation?" For the first edition of this workshop the chairs collected the following main topics of interest: • Semantic Annotation for understanding the content and context of social media streams. • Integration of Social Media with Linked Data. • Interactive Interfaces and visual analytics methodologies for managing multiple large-scale, dynamic, evolving datasets. • Stream reasoning and event detection. • Social Data Mining. • Collaborative tools and services for Citizens, Organisations, Communities. • Privacy, ethics, trustworthiness and legal issues in the Social Semantic Web. • Use case analysis, with specific interest for use cases that involve the application of Social Media and Linked Data methodologies in real-life scenarios. All of these, applied in the context of: • Crisis and Disaster Management • Emergency Response • Security and Citizen Journalism The workshop received 6 high-quality paper submissions and based on a thorough review process, thanks to our program committee, the decision was made to accept four of these papers for the workshop (67% acceptance rate). These four papers can be found later in this proceedings volume. Three out of four of these papers particularly discuss the integration and analysis of social media data, using Semantic Web technologies, e.g. for detecting complex events in social media streams, for visualizing and analysing sentiments with respect to certain topics in social media, or for detecting small-scale incidents entirely through the use of social media information. Finally, the fourth paper presents an architecture for using Semantic Web technologies in resource management during a disaster. Additionally, the workshop featured an invited keynote speech by Dr. Tomi Kauppinen from Aalto university. Dr. Kauppinen shared experiences from his work on applying Semantic Web technologies to application fields such as geoinformatics and scientific research, i.e. so-called Linked Science, but also recent ideas and applications in the emergency response field. His input was also highly valuable for the roadmapping discussion, which was held at the end of the workshop. A separate summary of the roadmapping session can be found at the end of these proceedings. Finally, we would like to thank our invited speaker Dr. Tomi Kauppinen, all our program committee members, as well as the workshop chair of ESWC2013, Johanna Völker (University of Mannheim), for helping us to make this first SMILE workshop a highly interesting and successful event!

Keyboard warriors in cyberfights:conflict in online communities of consumption

Nowadays, with the use of social media generalizing, increasingly more people gather online to share their passion for specific consumption activities. Despite this shared passion, conflicts frequently erupt in online communities of consumption (OCC). A systematic review of the literature revealed that a lot of knowledge has developed on OCC conflict. Different types of conflicts unfolding in an OCC context have been distinguished, various drivers of conflict identified and various consequences outlined at the individual level (experiential value) and the community level (collective engagement and community culture). However the specificity of conflicts unfolding in an OCC context has not been conceptualized. Past research is also inconclusive as to where and when does OCC conflict create or destroy value in communities. This research provides a theory of OCC conflict and its impact on value formation by conceptualizing OCC conflict as performances. The theory was developed by conducting a netnography of a clubbing forum. Close to 20,000 forum posts and 250 pages of interview transcript and field notes were collected over 27 months and analysed following the principles of grounded theory. Four different types of conflict performances are distinguished (personal, played, reality show and trolling conflict) based on the clarity of the performance. Each type of conflict performance is positioned with regard to its roots and consequences for value formation. This research develops knowledge on disharmonious interactions in OCCs contributing to the development of a less utopian perspective of OCCs. It indicates how conflict is not only a byproduct of consumption but it is also a phenomenon consumed. It also introduces the concept of performance clarity to the literature on performance consumption. This research provides guidelines to community managers on how to manage conflict and raises ethical issues regarding the management of conflict on social media.

Pub crawling at scale:tapping untappd to explore social drinking

There has been a recent surge of research looking at the reporting of food consumption on social media. The topic of alcohol consumption, however, remains poorly investigated. Social media has the potential to shed light on a topic that, traditionally, is difficult to collect fine-grained information on. One social app stands out in this regard: Untappd is an app that allows users to ‘check-in’ their consumption of beers. It operates in a similar fashion to other location-based applications, but is specifically tailored to the collection of information on beer consumption. In this paper, we explore beer consumption through the lens of social media. We crawled Untappd in real time over a period of 112 days, across 40 cities in the United States and Europe. Using this data, we shed light on the drinking habits of over 369k users. We focus on per-user and per-city characterisation, highlighting key behavioural trends.