Terminology mining in social media
Number of Authors: 2
2009 (English)Conference paper (Refereed)
The highly variable and dynamic word usage in social media presents serious challenges for both research and those commercial applications that are geared towards blogs or other user-generated non-editorial texts. This paper discusses and exempliﬁes a terminology mining approach for dealing with the productive character of the textual environment in social media. We explore the challenges of practically acquiring new terminology, and of modeling similarity and relatedness of terms from observing realistic amounts of data. We also discuss semantic evolution and density, and investigate novel measures for characterizing the preconditions for terminology mining.
Place, publisher, year, edition, pages
2009, 1. , 10 p.
Word Space, Distributional Semantics, Random Indexing, Terminology Mining, Social Media, Language Technology, Linguistics
Computer and Information Science
IdentifiersURN: urn:nbn:se:ri:diva-23546OAI: oai:DiVA.org:ri-23546DiVA: diva2:1042622
The 18th ACM Conference on Information and Knowledge Management (CIKM 2009), 2-5 November 2009, Hong Kong