Twitter data has been used for crime trend prediction (Aghababaei & Makrehchi, 2017). Only Twitter data and no other data has been used for prediction. Crime indices for different crimes are calculated using Twitter data collected over time. Then it is used to predict the crime index for the different crimes for the test data. The change in the crime index shows the change in trend for the crime either from decreasing to increasing or increasing to decreasing. This change is crime index can be used to find the crime which has an increasing trend and to implement measures to prevent and reduce it. Twitter data on the wholescale may reflect the day-to-day activities of the user. If the user posts GPS tagged tweets from various places he visits daily, then by analyzing the tweets it is possible to find the routine activities of the user. By extracting such a pattern from the collected Twitter data and analyzing them using routine activity theory it is possible to predict crime trends (Al Boni & Gerber, 2017). Though the daily activities of the users were considered the sequence in which these activities were done was not considered. So the prediction could be improved by considering the sequence of the activities.