Discovering User-Interest Topics on social media by Correlation
DOI:
https://doi.org/10.24311/jabes/2023.34.5.2Keywords:
Interest, Social media, Wikipedia, TF.IDF, CorrelationAbstract
Discovering user’s interests on social media was an issue that has received a lot of attention recently because it has high applicability in practice. The purpose of this paper is to introduce a method to detect user interest topics on social media by analyzing the content of user posts. In this paper, a semantic expansion technique based on Wikipedia and TF.IDF weighted vector representation, then estimated based on Pearson correlation. The result of the experiment shows that the method of topic detection can be applied to many different social media sites regardless of their structure, language, and links.
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