An intelligent system for predicting location from text content on social media

Sedef Demirci, S. Özdemir
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Abstract

In this study, we have presented an approach to show how location detection can be possible by using social media posts of Internet users. To this end, we have developed a software program to show that locations of Twitter users can be detected just by analyzing the contents of their tweets, even if they hide the location data coming from the background of the tweet. We have collected text-based data from Twitter which are posted by users in İstanbul, Ankara, and İzmir, the largest cities of Turkey according to population. After presenting the preprocessed data in vector space model, we have trained our system using the data by means of Naive Bayes Classifier. After the testing process, experimental results have shown that locations of Twitter users can be detected just by analyzing the contents of their publicly available tweets in the absence of location data with 54.57% accuracy rate for the mentioned three cities of Turkey.
从社交媒体上的文本内容预测位置的智能系统
在这项研究中,我们提出了一种方法来展示如何通过使用互联网用户的社交媒体帖子来实现位置检测。为此,我们开发了一个软件程序,表明即使Twitter用户隐藏了来自tweet背景的位置数据,也可以通过分析Twitter用户的tweet内容来检测其位置。我们从Twitter上收集了土耳其人口最多的城市İstanbul、安卡拉和İzmir的用户发布的文本数据。在向量空间模型中呈现预处理数据后,我们使用朴素贝叶斯分类器对系统进行训练。经过测试过程,实验结果表明,在没有位置数据的情况下,仅通过分析Twitter用户公开发布的推文内容就可以检测到Twitter用户的位置,对于上述三个土耳其城市,准确率为54.57%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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