A fuzzy logic-based text classification method for social media

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. This work compares 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.

Name thesis:degree_name

Master of Science in Electrical Engineering - (M.S.)

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Year

2017

Author dc:creator

• Wu, Keyuan

Contributors dc:contributor

• MengChu Zhou
• Ali Abdi
• Hesuan Hu

• Social media
• Text classification
• Fuzzy logic
• Electrical and Electronics

Repository record dc:identifier

https://digitalcommons.njit.edu/theses/31

OAI identifier oai:identifier

oai:digitalcommons.njit.edu:theses-1030