Sentiment Analysis Combination in Terrorist Detection on Twitter: A Brief Survey of Approaches and Techniques

摘要

Terrorism is a big concern for many governments and people, especially with using social media such as Twitter that uses new technologies. Terrorism uses many techniques to carry out their actions and plans. Technology can play an important role in providing accurate predictions of terrorist activities. Here, we tried to do so using sentiment analysis for terrorist-related of Twitter because the early detection of terrorist activity is very important to the recent attack and to combat the spread of global terrorist activity. This work studied the techniques of effective analysis of terrorist activity data on Twitter. It is based on 17 articles that used Twitter to study terrorism for different purposes, while highlighting the different techniques used, from this survey one can notice that the machine learning techniques were used the most for sentimental analysis with good accuracy depending on the data used such as AdaBoost, support vector machine, maximum entropy, Naive Bayes, decision tree algorithms. Few number of papers are analyzed tweets in Arabic language as compared to English version because of its complexity parsing beside the complexity in analyzing feelings in Arabic makes tasks more challenging.