Download full text
(653.0Kb)
Citation Suggestion
Please use the following Persistent Identifier (PID) to cite this document:
https://nbn-resolving.org/urn:nbn:de:0168-ssoar-66085-7
Exports for your reference manager
The Wisdom of the Audience: An Empirical Study of Social Semantics in Twitter Streams
[collection article]
Abstract Interpreting the meaning of a document represents a fundamental challenge for current semantic analysis methods. One interesting aspect mostly neglected by existing methods is that authors of a document usually assume certain background knowledge of their intended audience. Based on this knowledge, ... view more
Interpreting the meaning of a document represents a fundamental challenge for current semantic analysis methods. One interesting aspect mostly neglected by existing methods is that authors of a document usually assume certain background knowledge of their intended audience. Based on this knowledge, authors usually decide what to communicate and how to communicate it. Traditionally, this kind of knowledge has been elusive to semantic analysis methods. However, with the rise of social media such as Twitter, background knowledge of intended audiences (i.e., the community of potential readers) has become explicit to some extents, i.e., it can be modeled and estimated. In this paper, we (i) systematically compare different methods for estimating background knowledge of different audiences on Twitter and (ii) investigate to what extent the background knowledge of audiences is useful for interpreting the meaning of social media messages. We find that estimating the background knowledge of social media audiences may indeed be useful for interpreting the meaning of social media messages, but that its utility depends on manifested structural characteristics of message streams.... view less
Keywords
twitter; expertise; semantics; Internet; social network; collective knowledge; computer-mediated communication; meaning; comparison of methods; internet community
Classification
Natural Science and Engineering, Applied Sciences
Interactive, electronic Media
Free Keywords
Background Knowledge; Topic Model; Latent Dirichlet Allocation; Twitter Message; Audience User; Semantic Web
Collection Title
The Semantic Web: Semantics and Big Data; 10th International Conference, ESWC 2013, Montpellier, France, May 26-30, 2013: Proceedings
Editor
Cimiano, Philipp; Corcho, Oscar; Presutti, Valentina; Hollink, Laura; Rudolph, Sebastian
Conference
10. The Semantic Web: Semantics and Big Data (ESWC 2013). Montpellier, 2013
Document language
English
Publication Year
2013
Publisher
Springer
City
Berlin
Page/Pages
p. 502-516
Series
Lecture Notes in Computer Science (LNCS), 7882
DOI
https://doi.org/10.1007/978-3-642-38288-8_34
ISSN
1611-3349
ISBN
978-3-642-38288-8
Status
Published Version; peer reviewed
Licence
Deposit Licence - No Redistribution, No Modifications