Structure and evolution of blogspace

By Ravi Kumar, Jasmine Novak, Prabhakar Raghavan, Andrew Tomkins. 2004

407 citations recorded by the source corpus.

Subfields: Communication, Statistical and Nonlinear Physics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Communication

In Statistical and Nonlinear Physics

Citations in the corpus

Key differences between Web 1.0 and Web 2.0 (2008, neutral): “[1, 12, 14, 15, 16, 18].”
Age Prediction in Blogs: A Study of Style, Content, and Online Behavior in Pre- and Post-Social Media Generations (2011, background): “Furthermore, an early study on the LiveJournal demographic (Kumar et al., 2004) reported that 28.6% of blogs are written by bloggers between the ages 13-18 whereas based on the current demographic statistics, in 20102, only 6.96% of blogs are written by that age group and the number of bloggers in…”
Widespread Worry and the Stock Market (2010, background): “It seems reasonable to us that the noise will end up uniformly distributed in time.”
The strengths, weaknesses, opportunities and threats of using social software in higher and further education teaching and learning (2010, background): “Even in the case of blogs, which are largely maintained by individuals, the true value is derived from the comments of visitors or readers and the hyperlinks with other blogs (Kumar, Novak, Raghavan, & Tomkins, 2004).”
Personal information of adolescents on the Internet: A quantitative content analysis of MySpace. (2008, background): “They also discovered that 70% of friendships can be explained by one of three factors: age, location, and expressed shared interest(s) (Kumar et al., 2004).”
Wherefore art thou r3579x?: anonymized social networks, hidden patterns, and structural steganography (2007, background): “…Research Dept. of Computer Science Cornell University, Ithaca NY Cornell University, Ithaca NY dwork@microsoft.com lars@cs.cornell.edu kleinber@cs.cornell.edu ABSTRACT In a social network, nodes correspond to people or other social entities, and edges correspond to social links between them.”
A probabilistic approach to spatiotemporal theme pattern mining on weblogs (2006, background): “3) The interlinking structure of weblogs usually forms localized micro communities, reflecting relations such as friendship and location proximity [17].”
Meme-tracking and the dynamics of the news cycle (2009, background): “Some of the key research issues here have been the identification of topics over time [5, 11, 16], the evolving practices of bloggers [25, 26], the cascading adoption of stories [3, 14, 20, 23], and the ideological di-”
ARSA: a sentiment-aware model for predicting sales performance using blogs (2007, methodology): “Training an S-PLSA model on the blog data enables us to obtain a succinct summary of the sentiment information embedded in the blogs.”
The predictive power of online chatter (2005, background): “The structure and evolution of blogs were explored in [16] [17] [18] [1] .”
Group formation in large social networks: membership, growth, and evolution (2006, methodology): “The same technique has since been used for finding term bursts in a range of other domains, for instance to detect current topics in blogs [24].”
Joint Link Prediction and Attribute Inference Using a Social-Attribute Network (2014, background): “Other evidence of interaction [Kumar et al. 2004; Kim and Leskovec 2011] shows that users with similar attributes, or in some cases antithetical attributes, are likely to link to one another, motivating the use of attribute information for link prediction.”
Correlating financial time series with micro-blogging activity (2012, background): “[20] present a work on the evolution of social networks in the blogosphere.”
Factors Affecting Bloggers' Knowledge Sharing: An Investigation Across Gender (2011, background): “Indeed, “Web friendship” among bloggers connects each interest group in the blogosphere [62]. these friendships, in turn, generate peer pressure among bloggers to post and share their knowledge within their interest group [77].”
Wherefore Art Thou R3579x? Anonymized Social Networks, Hidden Patterns, and Structural Steganography (background): “While a number of these on-line data sources are based on publicly crawlable blogging and social networking sites [6] [20] [22], where users have explicitly chosen to publish their links to others, many of the most promising opportunities for the study of social networks are emerging from data on…”