Relevancer: Finding and labeling relevant information in tweet collections
Berlijn : Springer International publishing
InLecture Notes in Computer Science, (2016)Spiro, E.; Ahn, Y.Y. (ed.), Social Informatics. SocInfo 2016. Part II, pp. 210-224
8th International Conference on Social Informatics (SocInfo 2016), 11 november 2016
Article in monograph or in proceedings
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Communicatie- en informatiewetenschappen
Lecture Notes in Computer Science
Spiro, E.; Ahn, Y.Y. (ed.), Social Informatics. SocInfo 2016. Part II
SubjectLanguage & Speech Technology; Language in Society; Nederlab; Project in ADNEXT (Commit); Nederlab
We introduce a tool that supports knowledge workers who want to gain insights from a tweet collection, but due to time constraints cannot go over all tweets. Our system first pre-processes, de-duplicates, and clusters the tweets. The detected clusters are presented to the expert as so-called information threads. Subsequently, based on the information thread labels provided by the expert, a classifier is trained that can be used to classify additional tweets. As a case study, the tool is evaluated on a tweet collection based on the key terms ‘genocide’ and ‘Rohingya’. The average precision and recall of the classifier on six classes is 0.83 and 0.82 respectively. At this level of performance, experts can use the tool to manage tweet collections efficiently without missing much information.
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