6 research outputs found
Multi-dimensional Conversation Analysis across Online Social Networks
With the advance of the Internet, ordinary users have created multiple
personal accounts on online social networks, and interactions among these
social network users have recently been tagged with location information. In
this work, we observe user interactions across two popular online social
networks, Facebook and Twitter, and analyze which factors lead to retweet/like
interactions for tweets/posts. In addition to the named entities, lexical
errors and expressed sentiments in these data items, we also consider the
impact of shared user locations on user interactions. In particular, we show
that geolocations of users can greatly affect which social network post/tweet
will be liked/ retweeted. We believe that the results of our analysis can help
researchers to understand which social network content will have better
visibility.Comment: Datasets will be anonymized and published at:
http://akcora.wordpress.com/2013/12/24/pointer-for-datasets
Profiling user interactions on online social networks.
Over the last couple of years, there has been signi_cant research e_ort in mining user behavior on online social networks for applications ranging from sentiment analysis to marketing. In most of those applications, usually a snapshot of user attributes or user relationships are analyzed to build the data mining models, without considering how user attributes and user relationships can be utilized together.
In this thesis, we will describe how user relationships within a social network can be further augmented by information gathered from user generated texts to analyze large scale dynamics of social networks. Speci_cally, we aim at explaining social network interactions by using information gleaned from friendships, pro_les, and status posts of users. Our approach pro_les user interactions in terms of shared similarities among users, and applies the gained knowledge to help users in understanding the inherent reasons, consequences and bene_ts of interacting with other social network users