Navegando por Autor "Cha, Meeyoung"
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Item Characterizing user navigation and interactions in online social networks.(2012) Souza, Fabrício Benevenuto de; Rodrigues, Tiago; Cha, Meeyoung; Almeida, Virgílio Augusto FernandesUnderstanding how users navigate and interact when they connect to socialnetworking sites creates opportunities for better interface design, richer studies of social interactions, and improved design of content distribution systems. In this paper, we present an in-depth analysis of user workloads in online social networks. This 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 gather 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’ and non-immediate friends’ pages. Results show 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, silent interactions like browsing friends’ pages increase the measured level of interaction among users. Additionally, we find that friends requesting content are often within close geographical proximity of the uploader. We also discuss a series of implications of our findings for efficient system and interface design as well as for advertisement placement in online social networks.Item Delayed information cascades in Flickr : measurement, analysis, and modeling.(2012) Cha, Meeyoung; Souza, Fabrício Benevenuto de; Ahn, Yong-Yeol; Gummadi, Krishna P.Online social networks exhibit small-world network characteristics, implying that information can spread in the network quickly and widely. This ability to spread information rapidly has led to high expectations for word-of-mouth and viral campaigns in online social networks. However, a recent study of the Flickr social network has shown that popular photos do not spread as quickly as one might expect, but show a steady linear growth of popularity over several years. In this paper, we investigate possible reasons for this delay in word-of-mouth propagation by studying the behavior of Flickr users. We identify two factors of a social network that can alter how information spreads: the burstiness of user login times and content aging. We study the impact of these factors using an epidemiological model that was adapted to allow us to investigate the speed of propagation in word-ofmouth propagation. Our simulation shows that the two factors can explain the patterns observed on the real data and help us to understand how these factors affect a small-world network’s ability to spread information quickly and widely.