Predicting the Tweet Location Based on KNN-Sentimental Analysis (original) (raw)

2020 15th International Conference on Computer Engineering and Systems (ICCES), 2020

Abstract

Geographical information is important in several applications, such as, advertising and recommending. Despite the availability and the existence of social media, especially twitter, the geographical coordinates are often hidden according to privacy reasons. In this paper, a new model is proposed to predict the tweet location based on the KNN-Sentimental Analysis (KNNSA) model. Predicting the tweet location based on the KNN-sentiment analysis (KNNSA) model extracts text features from the tweet in addition to the date and time features. Then, applying sentimental analysis and classifying the data by K-nearest neighbors (KNN) classifier. The (KNNSA) model is evaluated and compared to the previous work and it achieves better performance in terms of root mean squared error (RMSE) and of the mean absolute error (MAE).

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