Abstract
In this paper, we propose and apply a method to analyze the activeness of an event based on related tweets. The method characterizes and measures activeness of an event by a set of indicators. The indicators proposed in this paper are original tweet count, retweet count, follower count, positive sentiment, negative sentiment, daily change in users count, and sparseness of user community. We present procedures to compute the last two indicators. All indicators collectively are used to determine the activeness of an event. This approach is used to analyze the Syrian-refugee-crisis-related tweets. Its generality is demonstrated by applying it to analyze “immigration”-related tweets.
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Karsten Ladner was supported by NSF REU site grant.
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Appendix
Appendix
In this appendix, we provide the results of our analysis based on data collected during May 31 through July 16, 2018. Due to system problems, data were not available on some days. So we were unable to perform daily analysis reliably. The summary of results is provided. Figure 30 compares the tweet sentiments from different countries on three different random days. It can be seen that USA dominates on all 3 days. As we considered only English tweets, countries from the Middle East appear in yellow region.
Figure 31 shows the tweets originating from countries where English is spoken. As can be seen, most tweets originate from the USA. Figure 32 shows the states from where the tweets are originating.
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Ladner, K., Ramineni, R. & George, K.M. Activeness of Syrian refugee crisis: an analysis of tweets. Soc. Netw. Anal. Min. 9, 61 (2019). https://doi.org/10.1007/s13278-019-0606-6
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DOI: https://doi.org/10.1007/s13278-019-0606-6