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

Autor:	Sakthi Balan Muthiah, Nirmal Kumar Sivaraman, Vibhor Agarwal, Yash Vekaria
Rok vydání:	2021
Předmět:	Metadata Generality Information retrieval Computer science Event (computing) Factor (programming language) Social media Herding computer Social network analysis computer.programming_language
Zdroj:	Research Challenges in Information Science ISBN: 9783030750176 RCIS
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::49437ccf0cd9b109cfb9ae71e05e853d https://doi.org/10.1007/978-3-030-75018-3_47 Zobrazit plný text záznamu