Conference Proceedings

Modeling evolution of topics in large-scale temporal text corpora

E Momeni, S Karunasekera, P Goyal, K Lerman

12th International AAAI Conference on Web and Social Media, ICWSM 2018 | Published : 2018

Abstract

Copyright © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. Large text temporal collections provide insights into social and cultural change over time. To quantify changes in topics in these corpora, embedding methods have been used as a diachronic tool. However, they have limited utility for modeling changes in topics due to the stochastic nature of training. We propose a new computational approach for tracking and detecting temporal evolution of topics in a large collection of texts. This approach for identifying dynamic topics and modeling their evolution combines the advantages of two methods: (1) word embeddings to learn contextual s..

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