Prediction of places of visit using tweets

We study the problem of predicting likely places of visit of users using their past tweets

Arun Chauhan; Krishna Kummamuru; Durga Toshniwal

2016

Scholarcy highlights

  • We study the problem of predicting likely places of visit of users using their past tweets
  • We propose a novel approach for predicting place of visit within a given geospatial range considering the past tweets and the time of visit
  • We analyze use of various features that can be extracted from the historical tweets—for example, personality traits estimated from the past tweets and the actual words mentioned in the tweets
  • We performed extensive empirical experiments involving, real data derived from twitter timelines of 4600 persons with multi-label classification as predictive model
  • Based on our experimental study, we come up with general guidelines on building the prediction model in terms of the type of features extracted from historical tweets, window size of historical tweets and on the optimal radius of query around the place of visit at a given time
  • In: Proceedings of the 36th international ACM SIGIR conference on research and development in information retrieval

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