DocumentCode
141816
Title
A hashtags dictionary from crowdsourced definitions
Author
Ghenname, Merieme ; Subercaze, Julien ; Gravier, Christophe ; Laforest, Frederique ; Abik, Mounia ; Ajhoun, R.
Author_Institution
LT2C, Univ. Jean Monnet, St. Etienne, France
fYear
2014
fDate
March 31 2014-April 4 2014
Firstpage
39
Lastpage
44
Abstract
Hashtags are user-defined terms used on the Web to tag messages like microposts, as featured on Twitter. Because a hashtag is a textual word, its representation does not convey all the concepts it embodies. Several online dictionaries have been manually and collaboratively built to provide natural language definitions of hashtags. Unfortunately, these dictionaries in their rough form are inefficient for their inclusion in automatic text processing systems. As hashtags can be polysemic, dictionaries are also agnostic to collision of hashtags. This paper presents our approach for the automatic structuration of hashtags definitions into synonym rings. We present the output as a so-called folksionary, i.e. a single integrated dictionary built from everybody´s definitions. For this purpose, we achieved a semantic-relatedness clustering to group definitions that share the same meaning.
Keywords
outsourcing; social networking (online); text analysis; Twitter; automatic text processing systems; crowdsourced definitions; folksionary; hashtags dictionary; natural language definitions; online dictionaries; semantic-relatedness clustering; synonym rings; textual word; Clustering algorithms; Context; Dictionaries; Knowledge based systems; Measurement; Natural languages; Prototypes;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering Workshops (ICDEW), 2014 IEEE 30th International Conference on
Conference_Location
Chicago, IL
Type
conf
DOI
10.1109/ICDEW.2014.6818300
Filename
6818300
Link To Document