Now showing 1 - 6 of 6
  • Publication
    The pursuit of happiness : searching for worthy followees on twitter
    (Intelligent Systems Research Centre, 2011-08-31) ; ;
    We are living in an age of information overload, where it can be difficult to define which information is relevant and important to the end user at a point in time. In this paper, we introduce a solution to apportioning this constant flow of information by going to the source of the content, namely the producers. This paper examines an application for searching for pertinent friends on the popular microblogging service, Twitter1 and our approach to curtail the cold start problem that new users of the service face. We introduce our search technology which is capable of finding the producers of wanted content and suggest connecting to them as followees on Twitter. We also prove the usefulness of this technology through the results of a live user experiment carried out on these cold start users.
      1629
  • Publication
    ThemeCrowds: Multiresolution Summaries of Twitter Usage
    (University College Dublin. School of Computer Science and Informatics, 2011-06) ; ; ; ;
    Users of social media sites, such as Twitter, rapidly generate large volumes of text content on a daily basis. Visual summaries are needed to understand what groups of people are saying collectively in this unstructured text data. Users will typically discuss a wide variety of topics, where the number of authors talking about a specific topic can quickly grow or diminish over time, and what the collective is saying about the subject can shift as a situation develops. In this paper, we present a technique that summarises what collections of Twitter users are saying about certain topics over time. As the correct resolution for inspecting the data is unknown in advance, the users are clustered hierarchically over a fixed time interval based on the similarity of their posts. The visualisation technique takes this data structure as its input. Given a topic, it finds the correct resolution of users at each time interval and provides tags to summarise what the collective is discussing. The technique is tested on three microblogging corpora, consisting of up to tens of millions of tweets and over a million users. We provide some preliminary user feedback from a research group interested in the area of social media analysis, where this tool could be applied.
      97
  • Publication
    Recommending twitter users to follow using content and collaborative filtering approaches
    Recently the world of the web has become more social and more real-time. Facebook and Twitter are perhaps the exemplars of a new generation of social, real-time web services and we believe these types of service provide a fertile ground for recommender systems research. In this paper we focus on one of the key features of the social web, namely the creation of relationships between users. Like recent research, we view this as an important recommendation problem for a given user, UT which other users might be recommended as followers/followees but unlike other researchers we attempt to harness the real-time web as the basis for profiling and recommendation. To this end we evaluate a range of different profiling and recommendation strategies, based on a large dataset of Twitter users and their tweets, to demonstrate the potential for effective and efficient followee recommendation.
      10040Scopus© Citations 397
  • Publication
    Finding useful users on twitter : twittomender the followee recommender
    This paper examines an application for finding pertinent friends (followees) on Twitter. Whilst Twitter provides a great basis for receiving information, we believe a potential downfall lies in the lack of an effective way in which users of Twitter can find other Twitter users to follow. We apply several recommendation techniques to build a followee recommender for Twitter. We evaluate a variety of different recommendation strategies, using real-user data, to demonstrate the potential for this recommender system to correctly identify and promote interesting users who are worth following.
      1862Scopus© Citations 42
  • Publication
    Recommending user connections by utilising the real-time Web
    (University College Dublin. School of Computer Science and Informatics, 2014) ;
    Social media services, such as Facebook and Twitter, thrive on user engagement around the active sharing and passive consumption of content. Many of these services have become an important way to discover relevant and interesting information in a timely manner. But to make the most of this aspect of these services it is important that users can locate and follow the most useful producers of relevant content. As these services have continued to grow rapidly this has become more and more of a challenge, especially for new users. This problem can be solved in principle by constructing a recommendation system based on a model of users' preferences and interests to recommend new users worth following.In this thesis we propose a recommendation framework for friend finding. It is capable of integrating different sources of user preference information that is available through services such as Twitter and related services. It is also designed to provide a natural partitioning of user interests based on those topics that are core to the user versus those that are more peripheral and the social connections linked with the user. This provides access to a range of different types of recommendation strategies that may be more helpful in focusing the search for relevant users according to different types of user interests. We demonstrate the effectiveness of our approach by evaluating recommendation quality across large sets of real-world users.
      474
  • Publication
    Personalized and automatic social summarization of events in video
    Social services like Twitter are increasingly used to provide a conversational backdrop to real-world events in real-time. Sporting events are a good example of this and this year, millions of users tweeted their comments as they watched the World Cup matches from around the world. In this paper, we look at using these time-stamped opinions as the basis for generating video highlights for these soccer matches. We introduce the PASSEV system and describe and evaluate two basic summarization approaches.
      1581Scopus© Citations 36