Fuzzy logic-based text classification method for social media data

Document Type

Conference Proceeding

Publication Date

11-27-2017

Abstract

Social media offer abundant information for studying people's behaviors, emotions and opinions during the evolution of various rare events such as natural disasters. It is useful to analyze the correlation between social media and human-affected events. This study uses Hurricane Sandy 2012 related Twitter text data to conduct information extraction and text classification. Considering that the original data contains different topics, we need to find the data related to Hurricane Sandy. A fuzzy logic-based approach is introduced to solve the problem of text classification. Inputs used in the proposed fuzzy logic-based model are multiple useful features extracted from each Twitter's message. The output is its degree of relevance for each message to Sandy. A number of fuzzy rules are designed and different defuzzification methods are combined in order to obtain desired classification results. We compare the proposed method with the well-known keyword search method in terms of correctness rate and quantity. The result shows that the proposed fuzzy logic-based approach is more suitable to classify Twitter messages than keyword word method.

Identifier

85044188867 (Scopus)

ISBN

[9781538616451]

Publication Title

2017 IEEE International Conference on Systems Man and Cybernetics Smc 2017

External Full Text Location

https://doi.org/10.1109/SMC.2017.8122902

First Page

1942

Last Page

1947

Volume

2017-January

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