Abstract
This study aims to predict the next location of a twitter user only by using his past tweets. Twitter is a very popular micro-blogging platform and a lot of people tweet about different topics varying from personal day-to-day activities to some global event. This provides us with the opportunity to perform sentiment analysis on their past tweets for prediction of their next visit. Sentiment analysis helps in revealing the opinion, desire or intentions of a person looking at the text that they write. In this paper, a new model called Sentiments based Labeled LDA model (SLLDA) is proposed to predict users’ next location within a given geo-spatial range. This kind of prediction can be used by various establishment owners for the targeted promotions of their products. This can also be helpful for personalized recommendation. Various experiments have been performed to evaluate the performance of the proposed model. The proposed model outperforms in every set of experiments and is better than each baseline model considered in the study. The accuracy comparison has also been done for different window lengths of past tweets and different radii of query. The performance of the proposed model turned out to be better for each set of experiments.
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Singh, R., Toshniwal, D. (2018). Location Prediction Using Sentiments of Twitter Users. In: Ordonez, C., Bellatreche, L. (eds) Big Data Analytics and Knowledge Discovery. DaWaK 2018. Lecture Notes in Computer Science(), vol 11031. Springer, Cham. https://doi.org/10.1007/978-3-319-98539-8_8
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