Abstract
Increase in Twitter's popularity has been phenomenal over time and the Tweets now, are not only a mean of status update and one-on-one communication but widely used for the trend setting and marketing. The probability that a Tweet will be seen by the user when he was offline is very low. In order to increase the throughput of the responses it is important to determine the number of individuals online so that the Tweet is seen by maximum number of users. This research focuses on identifying the individual users from Saudi Arabia based on the parameters already set for the conduct of this study. The time stamped data for 1000 selected individuals is retrieved from Twitter and their data is analyzed accordingly. The number of online users by recording the 'last seen' status are observed. The retrieval of data is based on number of experiments that were run on same time in all days of the week to reduce the inconsistent patterns. The data is then analyzed to see the time slots where the online user percentage is higher as compared to other time slots. The results of the study are focused to identify and recommended the timings when the Tweets are better valued and the impact is considerable.