Social architecture and the emergence of power laws in online social games

This paper explores the concept of the “social architecture” of games, and tests the theory that it is possible to analyse game mechanics based on the effect they have on the social behaviour of the players. Using tools from Social Network Analysis, these studies confirm that social activity in games reliably follows a power distribution: a few players are responsible for a disproportionate amount of social interactions. Based on this, the scaling exponent is highlighted as a simple measure of sociability that is constant for a game design. This allows for the direct comparison of social activity in very different games. In addition, it can act as a powerful analytical tool for highlighting anomalies in game designs that detrimentally affect players’ ability to interact socially. Although the social architectures of games are complicated systems, SNA allows for quantitative analysis of social behaviours of players in meaningful ways, which are to the benefit of game designers

Friend Suggestion and Friend Browsing in Web 2.0 Applications

Web 2.0 and social network applications have become increasingly popular. It is important for these applications to help users in maintaining their social networks by providing functions on friend suggestion and friend browsing. However, little study in this area has been reported in the literature. This paper proposes the design of two modules for friend suggestion and friend browsing. The first module is based on Hopfield Net spreading activation, while the second module is based on hyperbolic tree and self-organizing map. The proposed evaluation plan is also presented in the paper

A data-driven analysis to question epidemic models for citation cascades on the blogosphere

Citation cascades in blog networks are often considered as traces of information spreading on this social medium. In this work, we question this point of view using both a structural and semantic analysis of five months activity of the most representative blogs of the french-speaking community.Statistical measures reveal that our dataset shares many features with those that can be found in the literature, suggesting the existence of an identical underlying process. However, a closer analysis of the post content indicates that the popular epidemic-like descriptions of cascades are misleading in this context.A basic model, taking only into account the behavior of bloggers and their restricted social network, accounts for several important statistical features of the data.These arguments support the idea that citations primary goal may not be information spreading on the blogosphere.Comment: 18 pages, 9 figures, to be published in ICWSM-13 proceeding

Understanding Online Reputation Of Mediterranean Destinations

Destination managers are investing considerable efforts (i.e. time, resources and money) to market their destinations on the internet, often not considering the fact that unofficial information sources are gaining more and more popularity among internet users. Long tail players (such as blogs, wikis, reviews, etc.) are actually appearing in the ranking of search engines, spreading almost the same contents as the official sources, but with very different strategies, goals and styles. Starting from a log files analysis of a given Mediterranean destination, nine keywords have been used to perform search activities on two major search engines (Google and Yahoo!). A content analysis study has been performed on search results in order to examine topics and arguments of the retrieved results, which are shaping the web reputation of the destination. The paper shows that destinations need to manage their brand and online reputation holistically, by listening all players providing information about them, and trying to leverage on their contributions

Relating Group Size and Posting Activity of an Online Community of Financial Investors: Regularities and Seasonal Patterns

Group size can potentially affect collective activity and individual propensity to contribute to collective goods. Mancur Olson, in his Logic of Collective Action, argued that individual contribution to a collective good tends to be lower in groups of large size. Today, online communication platforms represent an interesting ground to study such collaborative dynamics under possibly different conditions (e.g., lower costs related to gather and share information). This paper examines the relationship between group size and activity in an online financial forum, where users invest time in sharing news, analysis and comments with other investors. We looked at about 24 million messages shared in more than ten years in the finanzaonline.com online forum. We found that the relationship between the number of active users and the number of posts shared by those users is of the power type (with exponent α\u3e1) and is subject to periodic fluctuations, mostly driven by hour-of-the-day and day-of-the-week effects. The daily patterns of the exponent showed a divergence between working week and weekend days. In general, the exponent was lower before noon, where investors are typically interested in market news, higher in the late afternoon, where markets are closing and investors need better understanding of the situation. Further research is needed, especially at the micro level, to dissect the mechanisms behind these regularities

Survey on Link Prediction and Page Ranking In Blogs S.Geetha

This paper presents a study of the various aspects of link prediction and page ranking in blogs. Social networks have taken on a new eminence from the prospect of the analysis of social networks, which is a recent area of research which grew out of the social sciences as well as the exact sciences, especially with the computing capacity for mathematical calculations and even modelling which was previously impossible. An essential element of social media, particularly blogs, is the hyperlink graph that connects various pieces of content. Link prediction has many applications, including recommending new items in online networks (e.g., products in eBay and Amazon, and friends in Face book), monitoring and preventing criminal activities in a criminal network, predicting the next web page users will visit, and complementing missing links in automatic web data crawlers. Page Rank is the technique used by Google to determine importance of page on the web. It considers all incoming links to a page as votes for Page Rank. Our findings provide an overview of social relations and we address the problem of page ranking and link prediction in networked data, which appears in many applications such as network analysis or recommended systems. Keywords- web log, social networks analysis, readership, link prediction, Page ranking. I

Socio-semantic dynamics in a blog network

The blogosphere can be construed as a knowledge network made of bloggers who are interacting through a social network to share, exchange or produce information. We claim that the social and semantic dimensions are essentially co-determined and propose to investigate the co-evolutionary dynamics of the blogosphere by examining two intertwined issues: First, how does knowledge distribution drive new interactions and thus influence the social network topology? Second, which role structural network properties play in the information circulation in the system? We adopt an empirical standpoint by analyzing the semantic and social activity of a portion of the US political blogosphere, monitored on a period of four months

Understanding Crowd-Powered Search Groups: A Social Network Perspective

Background: Crowd-powered search is a new form of search and problem solving scheme that involves collaboration among a potentially large number of voluntary Web users. Human flesh search (HFS), a particular form of crowd-powered search originated in China, has seen tremendous growth since its inception in 2001. HFS presents a valuable test-bed for scientists to validate existing and new theories in social computing, sociology, behavioral sciences, and so forth. Methodology: In this research, we construct an aggregated HFS group, consisting of the participants and their relationships in a comprehensive set of identified HFS episodes. We study the topological properties and the evolution of the aggregated network and different sub-groups in the network. We also identify the key HFS participants according to a variety of measures. Conclusions: We found that, as compared with other online social networks, HFS participant network shares the power-law degree distribution and small-world property, but with a looser and more distributed organizational structure, leading to the diversity, decentralization, and independence of HFS participants. In addition, the HFS group has been becoming increasingly decentralized. The comparisons of different HFS sub-groups reveal that HFS participants collaborated more often when they conducted the searches in local platforms or the searches requiring a certain level of professional knowledge background. On the contrary, HFS participants did not collaborate much when they performed the search tas

The spread of media content through blogs

Blogs are a popular way to share personal journals, discuss matters of public opinion, pursue collaborative conversations, and aggregate content on similar topics. Blogs can be also used to disseminate new content and novel ideas to communities of interest. In this paper, we present an analysis of the topological structure and the patterns of popular media content that is shared in blogs. By analyzing 8.7 million posts of 1.1 million blogs across 15 major blog hosting sites, we find that the network structure of blogs is “less social” compared to other online social networks: most links are unidirectional and the network is sparsely connected. The type of content that was popularly shared on blogs was surprisingly different from that from the mainstream media: user generated content, often in the form of videos or photos, was the most common type of content disseminated in blogs. The user-generated content showed interesting viral-spreading patterns within blogs. Topical content such as news and political commentary spreads quickly by the hour and then quickly disappears, while non-topical content such as music and entertainment propagates slowly over a much long period of time