While residential broadband Internet access is popular in many parts of the world, only a few studies have examined the characteristics of such traffic. In this paper we describe observations from monitoring the network activity for more than 20,000 residential DSL customers in an urban area. To ensure privacy, all data is immediately anonymized. We augment the anonymized packet traces with information about DSL-level sessions, IP (re-)assignments, and DSL link bandwidth. Our analysis reveals a number of surprises in terms of the mental models we developed from the measurement literature. For example, we find that HTTP—not peer-to-peer—traffic dominates by a significant margin; that more often than not the home user’s immediate ISP connectivity contributes more to the round-trip times the user experiences than the WAN portion of the path; and that the DSL lines are frequently not the bottleneck in bulk-transfer performance.

This paper investigates the uses of social networking site Facebook, and the gratifications users derive from those uses. In the first study, 137 users generated words or phrases to describe how they used Facebook, and what they enjoyed about their use. These phrases were coded into 46 items which were completed by 241 Facebook users in Study 2. Factor analysis identified seven unique uses and gratifications: social connection, shared identities, content, social investigation, social network surfing and status updating. User demographics, site visit patterns and the use of privacy settings were associated with different uses and gratifications. Author Keywords Social networking sites, uses and gratifications, motivation

Online social networking sites such as Facebook and MySpace have become increasingly popular, with close to 500 million users as of August 2008. The introduction of the Facebook Developer Platform and OpenSocial allows thirdparty developers to launch their own applications for the existing massive user base. The viral growth of these social applications can potentially influence how content is produced and consumed in the future Internet. To gain a better understanding, we conducted a largescale measurement study of the usage characteristics of online social network based applications. In particular, we developed and launched three Facebook applications, which have achieved a combined subscription base of over 8 million users. Using the rich dataset gathered through these applications, we analyze the aggregate workload characteristics (including temporal and geographical distributions) as well as the structure of user interactions. We explore the existence of ‘communities’, with high degree of interaction within a community and limited interaction outside the community. We find that a small fraction of users account for the majority of activity within the context of our Facebook applications and a small number of applications account for the majority of users on Facebook. Furthermore, user response times for Facebook applications are independent of source/destination user locality. We also investigate distinguishing characteristics of social gaming applications. To the best of our knowledge, this is the first study analyzing user activities on online social applications.

Understanding how users behave when they connect to social networking sites creates opportunities for better interface design, richer studies of social interactions, and improved design of content distribution systems. In this paper, we present a first of a kind analysis of user workloads in online social networks. Our study is based on detailed clickstream data, collected over a 12-day period, summarizing HTTP sessions of 37,024 users who accessed four popular social networks: Orkut, MySpace, Hi5, and LinkedIn. The data were collected from a social network aggregator website in Brazil, which enables users to connect to multiple social networks with a single authentication. Our analysis of the clickstream data reveals key features of the social network workloads, such as how frequently people connect to social networks and for how long, as well as the types and sequences of activities that users conduct on these sites. Additionally, we crawled the social network topology of Orkut, so that we could analyze user interaction data in light of the social graph. Our data analysis suggests insights into how users interact with friends in Orkut, such as how frequently users visit their friends ’ or non-immediate friends ’ pages. In summary, our analysis demonstrates the power of using clickstream data in identifying patterns in social network workloads and social interactions. Our analysis shows that browsing, which cannot be inferred from crawling publicly available data, accounts for 92 % of all user activities. Consequently, compared to using only crawled data, considering silent interactions like browsing friends ’ pages increases the measured level of interaction among users.

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History repeatedly demonstrates that rural communities have unique technological needs. Yet, we know little about how rural communities use modern technologies, so we lack knowledge on how to design for them. To address this gap, our empirical paper investigates behavioral differences between more than 3,000 rural and urban social media users. Using a dataset collected from a broadly popular social network site, we analyze users ’ profiles, 340,000 online friendships and 200,000 interpersonal messages. Using social capital theory, we predict differences between rural and urban users and find strong evidence supporting our hypotheses. Namely, rural people articulate far fewer friends online, and those friends live much closer to home. Our results also indicate that the groups have substantially different gender distributions and use privacy features differently. We conclude by discussing design implications drawn from our findings; most importantly, designers should reconsider the binary friend-or-not model to allow for incremental trust-building. Author Keywords Social media, rural, digital divide, social network sites

Social networking communities have become an important communications platform, but the popularity of these communities has also made them targets for a new breed of social spammers. Unfortunately, little is known about these social spammers, their level of sophistication, or their strategies and tactics. Thus, in this paper, we provide the first characterization of social spammers and their behaviors. Concretely, we make two contributions: (1) we introduce social honeypots for tracking and monitoring social spam, and (2) we report the results of an analysis performed on spam data that was harvested by our social honeypots. Based on our analysis, we find that the behaviors of social spammers exhibit recognizable temporal and geographic patterns and that social spam content contains various distinguishing characteristics. These results are quite promising and suggest that our analysis techniques may be used to automatically identify social spam. 1

Computer-mediated communication systems can be used to bridge the gap between doctors in underserved regions with local shortages of medical expertise and medical specialists worldwide. To this end, we describe the design of a prototype remote consultation system intended to provide the social, institutional and infrastructural context for sustained, self-organizing growth of a globally-distributed Ghanaian medical community. The design is grounded in an iterative design process that included two rounds of extended design fieldwork throughout Ghana and draws on three key design principles (social networks as a framework on which to build incentives within a self-organizing network; optional and incremental integration with existing referral mechanisms; and a weakly-connected, distributed architecture that allows for a highly interactive, responsive system despite failures in connectivity). We discuss initial experiences from an ongoing trial deployment in southern Ghana. Author Keywords Telemedicine, social networking, organizational interfaces,

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We study the characteristics of large online social networks through an extensive analysis of over 1.9 million MySpace profiles in an effort to understand who is using these networks and how they are being used. We study MySpace through a comparative study over three different, but related, facets: (i) the sociability of users in MySpace based on relationship, messaging, and group participation; (ii) the demographic characteristics of MySpace users in terms of age, gender, and location, and a study of how these factors correlate with their privacy preferences; and (iii) the text artifacts of MySpace users, which can be used to construct language models that distinguish MySpace users not just by who they say they are but also by the language model they employ. We find a number of surprising results and conjecture several potential research directions based on our observations.