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


Copyright © 2018, Association for the Advancement of Artificial Intelligence ( 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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