A Metadata-Based Event Detection Method Using Temporal Herding Factor and Social Synchrony on Twitter Data

Nirmal Kumar Sivaraman, Vibhor Agarwal, Yash Vekaria, Sakthi Balan Muthiah

Abstract: Detecting events from social media data is an important problem. In this paper, we propose a novel method to detect events by detecting traces of herding in the Twitter data. We analyze only the metadata for this and not the content of the tweets. We evaluate our method on a dataset of 3.3 million tweets that was collected by us. We then compared the results obtained from our method with a state of the art method called Twitinfo on the above mentioned 3.3 million dataset. Our method showed better results. To check the generality of our method, we tested it on a publicly available dataset of 1.28 million tweets and the results convey that our method can be generalised.