@inproceedings{4cf718ddef354c4fb44a85bc4c76ccf4,
title = "Identifying important life events from Twitter using semantic and syntactic patterns",
abstract = "Identifying global events from social media has been the focus of much research in recent years. However, the identification of personal life events poses new requirements and challenges that have received relatively little research attention. In this paper we explore a new approach for life event identification, where we expand social media posts into both semantic, and syntactic networks of content. Frequent graph patterns are mined from these networks and used as features to enrich life-event classifiers. Results show that our approach significantly outperforms the best performing baseline in accuracy (by 4.48% points) and F-measure (by 4.54% points) when used to identify five major life events identified from the psychology literature: Getting Married, Having Children, Death of a Parent, Starting School, and Falling in Love. In addition, our results show that, while semantic graphs are effective at discriminating the theme of the post (e.g. the topic of marriage), syntactic graphs help identify whether the post describes a personal event (e.g. someone getting married).",
keywords = "Classification, Event Detection, Frequent Pattern Mining, Semantic Networks, Social Media",
author = "Thomas Dickinson and Miriam Fernandez and Thomas, {Lisa A.} and Paul Mulholland and Pam Briggs and Harith Alani",
year = "2016",
month = jan,
day = "1",
language = "English",
series = "Proceedings of the 15th International Conference WWW/Internet 2016",
publisher = "International Association for the Development of the Information Society",
pages = "143--150",
editor = "Luis Rodrigues and Pedro Isaias",
booktitle = "Proceedings of the 15th International Conference WWW/Internet 2016",
note = "15th International Conference WWW/Internet 2016 ; Conference date: 28-10-2016 Through 30-10-2016",
}