Event Extraction from Telugu-English Code Mixed Social Media Text

Abstract

Natural Language Processing Event Extraction work is crucial. Social media has become increasingly significant in today's world. Using natural language, people can express their views on a wide range of topics on social media. Social Media tools popularized the devices among the masses making the information distribution faster and easier. The exchange of text is the most popular means of communication across social media users. It had become necessary to understand the semantics of messages communicated as the messages had a wide effect across the users. Event extraction means extracting the events across streams of the social media messages. Event extraction helps in taking corrective actions in case of natural calamities and hence possibly save the lives of many people. The major objective of the task is to draw specific knowledge to predict the events(incidents) specified in the code-mixed digital text. This paper proposes a two-step procedure for the extraction of the events. The first phase is by applying a binary classifier to identify the messages containing the event. The second phase is by applying a sequence labeling technique, conditional random fields (CRF), to extract the event from the message. As social media text is a bit noisy, it is a major challenge to develop learning algorithms for these tasks. Parts of Speech (POS) tags and Named Entity Recognition (NER) are used for the words to address some issues in this challenge.