Results 1 - 10
of
218
On the Evolution of User Interaction in Facebook
"... Online social networks have become extremely popular; numerous sites allow users to interact and share content using social links. Users of these networks often establish hundreds to even thousands of social links with other users. Recently, researchers have suggested examining the activity network— ..."
Abstract
-
Cited by 205 (6 self)
- Add to MetaCart
(Show Context)
Online social networks have become extremely popular; numerous sites allow users to interact and share content using social links. Users of these networks often establish hundreds to even thousands of social links with other users. Recently, researchers have suggested examining the activity network— a network that is based on the actual interaction between users, rather than mere friendship—to distinguish between strong and weak links. While initial studies have led to insights on how an activity network is structurally different from the social network itself, a natural and important aspect of the activity network has been disregarded: the fact that over time social links can grow stronger or weaker. In this paper, we study the evolution of activity between users in the Facebook social network to capture this notion. We find that links in the activity network tend to come and go rapidly over time, and the strength of ties exhibits a general decreasing trend of activity as the social network link ages. For example, only 30 % of Facebook user pairs interact consistently from one month to the next. Interestingly, we also find that even though the links of the activity network change rapidly over time, many graph-theoretic properties of the activity network remain unchanged.
Differences in the Mechanics of Information Diffusion Across Topics: Idioms, Political Hashtags, and Complex Contagion on Twitter. WWW
, 2011
"... ABSTRACT There is a widespread intuitive sense that different kinds of information spread differently on-line, but it has been difficult to evaluate this question quantitatively since it requires a setting where many different kinds of information spread in a shared environment. Here we study this ..."
Abstract
-
Cited by 171 (4 self)
- Add to MetaCart
(Show Context)
ABSTRACT There is a widespread intuitive sense that different kinds of information spread differently on-line, but it has been difficult to evaluate this question quantitatively since it requires a setting where many different kinds of information spread in a shared environment. Here we study this issue on Twitter, analyzing the ways in which tokens known as hashtags spread on a network defined by the interactions among Twitter users. We find significant variation in the ways that widely-used hashtags on different topics spread. Our results show that this variation is not attributable simply to differences in "stickiness," the probability of adoption based on one or more exposures, but also to a quantity that could be viewed as a kind of "persistence" -the relative extent to which repeated exposures to a hashtag continue to have significant marginal effects. We find that hashtags on politically controversial topics are particularly persistent, with repeated exposures continuing to have unusually large marginal effects on adoption; this provides, to our knowledge, the first large-scale validation of the "complex contagion" principle from sociology, which posits that repeated exposures to an idea are particularly crucial when the idea is in some way controversial or contentious. Among other findings, we discover that hashtags representing the natural analogues of Twitter idioms and neologisms are particularly non-persistent, with the effect of multiple exposures decaying rapidly relative to the first exposure. We also study the subgraph structure of the initial adopters for different widely-adopted hashtags, again finding structural differences across topics. We develop simulation-based and generative models to analyze how the adoption dynamics interact with the network structure of the early adopters on which a hashtag spreads.
What Do People Ask Their Social Networks, and Why? A Survey Study of Status Message Q&A Behavior
"... People often turn to their friends, families, and colleagues when they have questions. The recent, rapid rise of online social networking tools has made doing this on a large scale easy and efficient. In this paper we explore the phenomenon of using social network status messages to ask questions. W ..."
Abstract
-
Cited by 133 (11 self)
- Add to MetaCart
(Show Context)
People often turn to their friends, families, and colleagues when they have questions. The recent, rapid rise of online social networking tools has made doing this on a large scale easy and efficient. In this paper we explore the phenomenon of using social network status messages to ask questions. We conducted a survey of 624 people, asking them to share the questions they have asked and answered of their online social networks. We present detailed data on the frequency of this type of question asking, the types of questions asked, and respondents ‟ motivations for asking their social networks rather than using more traditional search tools like Web search engines. We report on the perceived speed and quality of the answers received, as well as what motivates people to respond to questions seen in their friends ‟ status messages. We then discuss the implications of our findings for the design of next-generation search tools. Author Keywords Social search, social networks, Q&A, Web search.
Signed networks in social media
- In Proc. 28th CHI
, 2010
"... Relations between users on social media sites often reflect a mixture of positive (friendly) and negative (antagonistic) interactions. In contrast to the bulk of research on social networks that has focused almost exclusively on positive interpretations of links between people, we study how the inte ..."
Abstract
-
Cited by 113 (9 self)
- Add to MetaCart
(Show Context)
Relations between users on social media sites often reflect a mixture of positive (friendly) and negative (antagonistic) interactions. In contrast to the bulk of research on social networks that has focused almost exclusively on positive interpretations of links between people, we study how the interplay between positive and negative relationships affects the structure of on-line social networks. We connect our analyses to theories of signed networks from social psychology. We find that the classical theory of structural balance tends to capture certain common patterns of interaction, but that it is also at odds with some of the fundamental phenomena we observe — particularly related to the evolving, directed nature of these on-line networks. We then develop an alternate theory of status that better explains the observed edge signs and provides insights into the underlying social mechanisms. Our work provides one of the first large-scale evaluations of theories of signed networks using on-line datasets, as well as providing a perspective for reasoning about social media sites. Author Keywords signed networks, structural balance, status theory, positive
Modeling relationship strength in online social networks.
- In Proc. WWW
, 2010
"... ABSTRACT Previous work analyzing social networks has mainly focused on binary friendship relations. However, in online social networks the low cost of link formation can lead to networks with heterogeneous relationship strengths (e.g., acquaintances and best friends mixed together). In this case, t ..."
Abstract
-
Cited by 109 (4 self)
- Add to MetaCart
(Show Context)
ABSTRACT Previous work analyzing social networks has mainly focused on binary friendship relations. However, in online social networks the low cost of link formation can lead to networks with heterogeneous relationship strengths (e.g., acquaintances and best friends mixed together). In this case, the binary friendship indicator provides only a coarse representation of relationship information. In this work, we develop an unsupervised model to estimate relationship strength from interaction activity (e.g., communication, tagging) and user similarity. More specifically, we formulate a link-based latent variable model, along with a coordinate ascent optimization procedure for the inference. We evaluate our approach on real-world data from Facebook and LinkedIn, showing that the estimated link weights result in higher autocorrelation and lead to improved classification accuracy.
Privacy wizards for social networking sites
- in WWW ’10: Proceedings of the 19th International World Wide Web Conference
, 2010
"... Privacy is an enormous problem in online social networking sites. While sites such as Facebook allow users fine-grained control over who can see their profiles, it is difficult for average users to specify this kind of detailed policy. In this paper, we propose a template for the design of a social ..."
Abstract
-
Cited by 95 (2 self)
- Add to MetaCart
(Show Context)
Privacy is an enormous problem in online social networking sites. While sites such as Facebook allow users fine-grained control over who can see their profiles, it is difficult for average users to specify this kind of detailed policy. In this paper, we propose a template for the design of a social networking privacy wizard. The intuition for the design comes from the observation that real users conceive their privacy preferences (which friends should be able to see which information) based on an implicit set of rules. Thus, with a limited amount of user input, it is usually possible to build a machine learning model that concisely describes a particular user’s preferences, and then use this model to configure the user’s privacy settings automatically. As an instance of this general framework, we have built a wizard based on an active learning paradigm called uncertainty sampling. The wizard iteratively asks the user to assign privacy “labels ” to selected (“informative”) friends, and it uses this input to construct a classifier, which can in turn be used to automatically assign privileges to the rest of the user’s (unlabeled) friends. To evaluate our approach, we collected detailed privacy preference data from 45 real Facebook users. Our study revealed two important things. First, real users tend to conceive their privacy preferences in terms of communities, which can easily be extracted from a social network graph using existing techniques. Second, our active learning wizard, using communities as features, is able to recommend high-accuracy privacy settings using less user input than existing policy-specification tools.
The Role of Social Networks in Information Diffusion
, 2012
"... Online social networking technologies enable individuals to simultaneously share information with any number of peers. Quantifying the causal effect of these mediums on the dissemination of information requires not only identification of who influences whom, but also of whether individuals would sti ..."
Abstract
-
Cited by 87 (3 self)
- Add to MetaCart
Online social networking technologies enable individuals to simultaneously share information with any number of peers. Quantifying the causal effect of these mediums on the dissemination of information requires not only identification of who influences whom, but also of whether individuals would still propagate information in the absence of social signals about that information. We examine the role of social networks in online information diffusion with a large-scale field experiment that randomizes exposure to signals about friends ’ information sharing among 253 million subjects in situ. Those who are exposed are significantly more likely to spread information, and do so sooner than those who are not exposed. We further examine the relative role of strong and weak ties in information propagation. We show that, although stronger ties are individually more influential, it is the more abundant weak ties who are responsible for the propagation of novel information. This suggests that weak ties may play a more dominant role in the dissemination of information online than currently believed.
Bridging the gap between physical location and online social networks
, 2010
"... This paper examines the location traces of 489 users of a location sharing social network for relationships between the users ’ mobility patterns and structural properties of their underlying social network. We introduce a novel set of locationbased features for analyzing the social context of a geo ..."
Abstract
-
Cited by 87 (8 self)
- Add to MetaCart
(Show Context)
This paper examines the location traces of 489 users of a location sharing social network for relationships between the users ’ mobility patterns and structural properties of their underlying social network. We introduce a novel set of locationbased features for analyzing the social context of a geographic region, including location entropy, which measures the diversity of unique visitors of a location. Using these features, we provide a model for predicting friendship between two users by analyzing their location trails. Our model achieves significant gains over simpler models based only on direct properties of the co-location histories, such as the number of co-locations. We also show a positive relationship between the entropy of the locations the user visits and the number of social ties that user has in the network. We discuss how the offline mobility of users can have implications for both researchers and designers of online social networks.
Social Network Activity and Social Well-Being
"... Previous research has shown a relationship between use of social networking sites and feelings of social capital. However, most studies have relied on self-reports by college students. The goals of the current study are to (1) validate the common self-report scale using empirical data from Facebook, ..."
Abstract
-
Cited by 70 (3 self)
- Add to MetaCart
Previous research has shown a relationship between use of social networking sites and feelings of social capital. However, most studies have relied on self-reports by college students. The goals of the current study are to (1) validate the common self-report scale using empirical data from Facebook, (2) test whether previous findings generalize to older and international populations, and (3) delve into the specific activities linked to feelings of social capital and loneliness. In particular, we investigate the role of directed interaction between pairs—such as wall posts, comments, and “likes”— and consumption of friends ’ content, including status updates, photos, and friends ’ conversations with other friends. We find that directed communication is associated with greater feelings of bonding social capital and lower loneliness, but has only a modest relationship with bridging social capital, which is primarily related to overall friend network size. Surprisingly, users who consume greater levels of content report reduced bridging and bonding social capital and increased loneliness. Implications for designs to support well-being are discussed. Author Keywords Social network sites, social capital, loneliness, computermediated communication
Tweet the debates: Understanding community annotation of uncollected sources
- In WSM ’09: Proceedings of the international workshop on Workshop on Social
, 2009
"... We investigate the practice of sharing short messages (microblogging) around live media events. Our focus is on Twitter and its usage during the 2008 Presidential Debates. We find that analysis of Twitter usage patterns around this media event can yield significant insights into the semantic structu ..."
Abstract
-
Cited by 69 (6 self)
- Add to MetaCart
(Show Context)
We investigate the practice of sharing short messages (microblogging) around live media events. Our focus is on Twitter and its usage during the 2008 Presidential Debates. We find that analysis of Twitter usage patterns around this media event can yield significant insights into the semantic structure and content of the media object. Specifically, we find that the level of Twitter activity serves as a predictor of changes in topics in the media event. Further we find that conversational cues can identify the key players in the media object and that the content of the Twitter posts can somewhat reflect the topics of discussion in the media object, but are mostly evaluative, in that they express the poster’s reaction to the media. The key contribution of this work is an analysis of the practice of microblogging live events and the core metrics that can leveraged to evaluate and analyze this activity. Finally, we offer suggestions on how our model of segmentation and node identification could apply towards any live, real-time arbitrary event.
