- General Chair:
- Aneesh Sharma,
- Program Chairs:
- Rakesh Agrawal,
- Matthias Grossglauser
Online Social Networks reach a significant and growing fraction of the population of the planet, and increasingly govern society's patterns of communication and information sharing. OSNs are now deeply woven into every major social process, and are transforming how politics, business, entertainment, surveillance, and advertisement operate. Their emergence has opened up new avenues for research at the intersection of computing and the social sciences, thanks in part to the efforts of scientists in curating large-scale behavioral datasets collected from these systems.
In light of these exciting trends, we would like to welcome you to the third edition of the ACM Conference on Online Social Networks (COSN), this year held at Stanford University. The program, featuring the presentation of 22 research papers along with two stellar keynote presentations by Jon Kleinberg and Alex Roetter, represents an eclectic mix of research in privacy, mobility, social epidemics and cascades, social media, network and group dynamics, and advances in the underlying theory, models, and algorithms. We trust you will find the program both intellectually stimulating and practically relevant.
We solicited full papers (up to 12 pages) describing original research in detail, and short papers (6 pages) conveying promising work and high-level vision. We received 82 submissions, of which 65 were full papers and 17 were short papers. We did not try to enforce a target mix of short and long papers, and the final program ended up containing 22 long papers. Interestingly, 9 of the 22 papers had authors from more than one continent. Attributing each paper to the continent with the most authors, the following geographic distribution results: North America: 11; South America: 1; Europe: 4; Asia: 6.
The PC consisted of 26 members (including the two of us). On average, every PC member reviewed around 10 papers and read a few more. We also sought advice from external reviewers for some papers as needed. Reviewing was single blind. The PC co-chairs refrained from submitting papers to the conference. In order to focus reviewer effort on the most difficult decisions, we early-rejected some papers after a first round with two reviews per paper. The remaining papers received at least one additional review. Reviewers were encouraged to use logarithmic scoring (1="bottom 50%", 2="top 50% but not top 25%", etc.) to keep scores from clustering around the average. We were careful to avoid conflicts in the review assignments, taking into account declarations of conflicts from both reviewers and authors. The reviewing process included extensive on-line discussions, followed by a full day face-to-face PC meeting, which took place at Stanford University on July 20th. The face-to-face PC meeting was attended by a large majority of the PC, and benefited from lively discussions and a great team spirit. We also held a one-day workshop on July 21st, chaired by Stelios Paparizos and attended by most PC members and a few invited guests interested in discussing trends and directions in the field. The Professor Ram Kumar Memorial Foundation bestowed several service awards to committee members to recognize their important contributions to the conference: Daniel R. Figueiredo and Krishna Gummadi for their contributions to committee deliberations; Krishna Gummadi for the best presentation during the "Trends and Directions" workshop; and Lucas Maystre for his management of the conference paper submission system.
Proceeding Downloads
Keynote: On-Line Social Systems with Long-Range Goals
Many systems involve the allocation of rewards for achievements, and these rewards produce a set of incentives that in turn guide behavior. Such effects are visible in many domains from everyday life, and they are increasingly forming a designed aspect ...
On Predictability of Rare Events Leveraging Social Media: A Machine Learning Perspective
Information extracted from social media streams has been leveraged to forecast the outcome of a large number of real-world events, from political elections to stock market fluctuations. An increasing amount of studies demonstrates how the analysis of ...
Tracking Triadic Cardinality Distributions for Burst Detection in Social Activity Streams
In everyday life, we often observe unusually frequent interactions among people before or during important events, i.e., people receive/send more greetings from/to their friends on Christmas Day than regular days. We also observe that some videos ...
Streaming Graph Partitioning in the Planted Partition Model
The sheer increase in the size of graph data has created a lot of interest into developing efficient distributed graph processing frameworks. Popular existing frameworks such as GraphLab and Pregel rely on balanced graph partitioning in order to ...
Who Contributes to the Knowledge Sharing Economy?
Information sharing dynamics of social networks rely on a small set of influencers to effectively reach a large audience. Our recent results and observations demonstrate that the shape and identity of this elite, especially those contributing original ...
Social Visibility and the Gifting of Digital Goods
One of the defining features of online social networks is that users' actions are visible to other users. In this paper, we argue that such social visibility has a detrimental effect on users' willingness to gift digital goods. The gift giving process ...
Identifying Personal Information in Internet Traffic
Users today access a multitude of online services---among the most popular of which are online social networks (OSNs)---via both web sites and dedicated mobile applications (apps), using a range of devices (traditional PCs, tablets, and smartphones) ...
The City Privacy Attack: Combining Social Media and Public Records for Detailed Profiles of Adults and Children
Data brokers have traditionally collected data from businesses, government records, and other publicly available offline sources. While each data source may provide only a few elements about a person's activities, data brokers combine these elements to ...
Impact of Clustering on the Performance of Network De-anonymization
Recently, graph matching algorithms have been successfully applied to the problem of network de-anonymization, in which nodes (users) participating in more than one social network are identified only by means of the structure of their links to other ...
Overlap Between Google and Bing Web Search Results!: Twitter to the Rescue?
Access to diverse perspectives nurtures an informed citizenry. Google and Bing have emerged as the duopoly that largely arbitrates which English language documents are seen by web searchers. We present our empirical study over the search results ...
Discovering Opinion Spammer Groups by Network Footprints
Online reviews are an important source for consumers to evaluate products/services on the Internet (e.g. Amazon, Yelp, etc.). However, more and more fraudulent reviewers write fake reviews to mislead users. To maximize their impact and share effort, ...
You Can Yak But You Can't Hide
The recent growth of anonymous messaging services -- such as 4chan, Whisper, and Yik Yak -- has brought online anonymity into the spotlight. Ideally, anonymous posts in principle allow for fully open discussion, and facilitate the sharing of ...
Towards Graph Watermarks
From network topologies to online social networks, many of today's most sensitive datasets are captured in large graphs. A significant challenge facing the data owners is how to share sensitive graphs with collaborators or authorized users, e.g. ISP's ...
Strength in Numbers: Robust Tamper Detection in Crowd Computations
- Bimal Viswanath,
- Muhammad Ahmad Bashir,
- Muhammad Bilal Zafar,
- Simon Bouget,
- Saikat Guha,
- Krishna P. Gummadi,
- Aniket Kate,
- Alan Mislove
Popular social and e-commerce sites increasingly rely on crowd computing to rate and rank content, users, products and businesses. Today, attackers who create fake (Sybil) identities can easily tamper with these computations. Existing defenses that ...
Diffusion Maximization in Evolving Social Networks
Diffusion in social networks has been studied extensively in the past few years. Most previous work assumes that the underlying network is a static object that remains unchanged as the diffusion process progresses. However, there are several real-life ...
Process-driven Analysis of Dynamics in Online Social Interactions
Measurement studies of online social networks show that all sociallinks are not equal, and the strength of each link is best characterized by the frequency of interactions between the linked users. To date, few studies have been able to examine detailed ...
Negative Messages Spread Rapidly and Widely on Social Media
We investigate the relation between the sentiment of a message on social media and its virality, defined as the volume and the speed of message diffusion. We analyze 4.1 million messages (tweets) obtained from Twitter. Although factors affecting message ...
Location Prediction: Communities Speak Louder than Friends
Humans are social animals, they interact with different communities of friends to conduct different activities. The literature shows that human mobility is constrained by their social relations. In this paper, we investigate the social impact of a ...
Not All Trips are Equal: Analyzing Foursquare Check-ins of Trips and City Visitors
Location-Based Social Networks (LBSN) such as Foursquare allow users to indicate venue visits via check-ins. This results in much fine grained context-rich data, useful for studying user mobility. In this work, we use check-ins to characterize trips and ...
"I don't have a photograph, but you can have my footprints.": Revealing the Demographics of Location Data
Location data are routinely available to a plethora of mobile apps and third party web services. The resulting datasets are increasingly available to advertisers for targeting and also requested by governmental agencies for law enforcement purposes. ...
Information Seeking and Responding Networks in Physical Gatherings: A Case Study of Academic Conferences in Twitter
With the allure of immediacy, social media like Twitter have been widely used in physical gatherings as a ``backchannel'' to facilitate the conversations among participants. Studies have been centered around identifying the characteristics of such ...
Mining User Deliberation and Bias in Online Newsgroups: A Dynamic View
Social media is changing many different aspects of our lives. By participating in online discussions, people exchange opinions on various topics, shape their stances, and gradually form their own characteristics. In this paper, we propose a framework ...
Dawn of the Selfie Era: The Whos, Wheres, and Hows of Selfies on Instagram
- Flávio Souza,
- Diego de Las Casas,
- Vinícius Flores,
- SunBum Youn,
- Meeyoung Cha,
- Daniele Quercia,
- Virgílio Almeida
Online interactions are increasingly involving images, especially those containing human faces, which are naturally attention grabbing and more effective at conveying feelings than text. To understand this new convention of digital culture, we study the ...
Characterizing Conversation Patterns in Reddit: From the Perspectives of Content Properties and User Participation Behaviors
It becomes the norm for people to communicate with one another through various online social channels, where different conversation structures are formed depending on platforms. One of the common online communication patterns is a threaded conversation ...
Sharing Topics in Pinterest: Understanding Content Creation and Diffusion Behaviors
- Jinyoung Han,
- Daejin Choi,
- A-Young Choi,
- Jiwon Choi,
- Taejoong Chung,
- Ted Taekyoung Kwon,
- Jong-Youn Rha,
- Chen-Nee Chuah
Pinterest provides a social curation service where people can collect, organize, and share content (pins in Pinterest) that reflect their interests. This paper investigates (1) the differences in pinning (i.e., the act of posting a pin) and repinning (...
Team Formation Dynamics: A Study Using Online Learning Data
Using data from online courses, we study the dynamics of team formation in online environments. In particular, we observe that the teams formed by online students for completing course projects are homogeneous in terms of age, location and education ...
Index Terms
- Proceedings of the 2015 ACM on Conference on Online Social Networks