Abstract
Social media becomes a part of our lives. People use different form of it to express their opinions on variety of ideas, events and facts. Twitter, as an example of such media, is commonly used to post short messages—tweets—related to variety of subjects. The paper proposes on application of fuzzy-based methodologies to process tweets, and to interpret information extracted from those tweets. We state that the obtained knowledge is fully explored and better comprehend when fuzziness is used. In particular, we analyze hashtags and keywords to extract useful knowledge. We look at the popularity of hashtags and changes of their popularity over time. Further, we process hashtags and keywords to build fuzzy signatures representing concepts associated with tweets.
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Shahbazova, S.N. (2020). Fuzziness in Information Extracted from Tweets’ Hashtags and Keywords. In: Shahbazova, S., Sugeno, M., Kacprzyk, J. (eds) Recent Developments in Fuzzy Logic and Fuzzy Sets. Studies in Fuzziness and Soft Computing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-030-38893-5_1
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DOI: https://doi.org/10.1007/978-3-030-38893-5_1
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