Publications
Search

Publications :: Search

Efficient Identification of Starters and Followers in Social Media

Show publication

On this page you see the details of the selected publication.

    Publication properties
    Title: Efficient Identification of Starters and Followers in Social Media
    Rating: (not rated yet)
    Discussion: 0 comments
    Date: 2009
    Publication type: Conference paper
    Authors:
    No. First name Last name Show
    1. Michael Mathioudakis
    2. Nick Koudas
    Download (by DOI): 10.1145/1516360.1516442
    BibTeX: conf/edbt/MathioudakisK09
    DBLP: db/conf/edbt/edbt2009.html#MathioudakisK09
    Bookmark:

    The following keywords have been assigned to this publication so far. If you have logged in, you can tag this publication with additional keywords.

    Keywords
    No keywords have been assigned to this publication yet.

    If you log in you can tag this publication with additional keywords

    A publication can refer to another publication (outgoing references) or it can be referred to by other publications (incoming references).

    Incoming References
    No incoming references have been assigned to this publication yet.
    Outgoing References
    No outgoing references have been assigned to this publication yet.

    If you log in you can add references to other publications

    A publication can be assigned to a conference, a journal or a school.

    Conference Track
    Conference Name: EDBT 2009, 12th International Conference on Extending Database Technology, Saint Petersburg, Russia, March 24-26, 2009 2009
    Track Name: Research
    URL: http://www.edbt.org/Proceedings/2009-StPetersburg/edbt/sessions/research.html

    Abstract
           Activity and user engagement in social media such as web logs,
           wikis, online forums or social networks has been increasing at
           unprecedented rates. In relation to social behavior in various
           human activities, user activity in social media indicates the
           existence of individuals that consistently drive or stimulate
           'discussions' in the online world. Such individuals are
           considered as 'starters' of online discussions in contrast with
           'followers' that primarily engage in discussions and follow
           them.
    
           In this paper, we formalize notions of 'starters' and
           'followers' in social media. Motivated by the challenging size
           of the available information related to online social behavior,
           we focus on the development of random sampling approaches
           allowing us to achieve significant efficiency while identifying
           starters and followers. In our experimental section we utilize
           BlogScope, our social media warehousing platform under
           development at the University of Toronto. We demonstrate the
           scalability and accuracy of our sampling approaches using real
           data establishing the practical utility of our techniques in a
           real social media warehousing environment.