Terminology mining in social media

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. Categories and Subject Descriptors H.3.1 [Content Analysis and Indexing]: Linguistic processing; I.2.7 [Natural Language Processing]: Text analysis; J.5 [Arts and Humanities]: Linguistics. General Terms Algorithms, Experimentation, Performance, Theory. Keywords Word Space, Distributional Semantics, Random Indexing, Terminology M...

• Type: Conference
• Year: 2009
• Where: CIKM
• Authors: Magnus Sahlgren, Jussi Karlgren
• Keywords: CIKM 2009, Information Management, Social Media, Terminology Mining, Terminology Mining Approach