A Method of Classification Twitter Posting Location for a Specific Space

KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KSE 2021)(2021)

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摘要
Under the definition of Baseball Stadium as a specific space, locations from which tweets relating to relevant spaces had been posted were classified whether inside or outside the specific space. As the classification method, BERT being one of the natural language processing models was employed. Through the comparison between the features of tweets inside and outside a specific space, it was revealed that there were differences between them in terms the number of URLs and media including photographs provided in them and shown that classification accuracy would improve by combining the numbers of URLs and media provided in tweets and their contents. In addition, through the extraction and comparison of words affecting the results of classification using LIME, what types of words and information had impacts on the judgement of classification were visualized. (C) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://crativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of KES International.
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关键词
social sensor, machine learning, classification, BERT, text mining, twitter, LIME, NLP
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