Daily Mean Similarity Scores for Twitter Trends
A Case Study to Reveal if an Area of Interest has a Trend in Ongoing Tweets Using Word and Sentence Embeddings
In this study, we have proposed an easily applicable automated methodology in which the daily mean similarity scores that show the similarity between the daily tweet corpus and the target words representing our area of interest is calculated by using a na\"ive correlation-based technique without training any machine learning model.The proposed methodology has mainly based on cosine similarity and word/sentence embeddings computed bymultilanguage universal sentence encoder and showed main opinion stream of the tweets with respect to a certain area of interest, which proves that an ongoing trend of a specific subject on twitter can easily be captured in almost realtime by using the proposed methodology in this study.
