학술논문

Measuring the Topical Specificity of Online Communities
Document Type
TEXT
Source
The Semantic Web: Semantics and Big Data; 10th International Conference, ESWC 2013, Montpellier, France, May 26-30, 2013: ProceedingsLecture Notes in Computer Science (LNCS) (7882)
Subject
Naturwissenschaften
Publizistische Medien, Journalismus,Verlagswesen
Online Community; Composite Function; Type Graph; Eigenvector Centrality; Concept Graph; Boards.ie
Naturwissenschaften, Technik(wissenschaften), angewandte Wissenschaften
interaktive, elektronische Medien
Netzgemeinschaft
Messung
Aktualität
Soziale Medien
Irland
Methodenvergleich
Experiment
Algorithmus
Science
News media, journalism, publishing
Natural Science and Engineering, Applied Sciences
Interactive, electronic Media
internet community
measurement
topicality
social media
Ireland
comparison of methods
experiment
algorithm
Language
English
Abstract
For community managers and hosts it is not only important to identify the current key topics of a community but also to assess the specificity level of the community for: a) creating sub-communities, and: b) anticipating community behaviour and topical evolution. In this paper we present an approach that empirically characterises the topical specificity of online community forums by measuring the abstraction of semantic concepts discussed within such forums. We present a range of concept abstraction measures that function over concept graphs - i.e. resource type-hierarchies and SKOS category structures - and demonstrate the efficacy of our method with an empirical evaluation using a ground truth ranking of forums. Our results show that the proposed approach outperforms a random baseline and that resource type-hierarchies work well when predicting the topical specificity of any forum with various abstraction measures.