@inproceedings{817c2cb1eef14f1f975e26793386da6f,
title = "Topic facet modeling: Semantic visual analytics for online discussion forums",
abstract = "In this paper, we propose a novel Topic Facet Model (TFM), a probabilistic topic model that assumes all words in single sentence are generated from one topic facet. The model is applied to automatically extract forum posts semantics for uncovering the content latent structures. We further prototype a visual analytics interface to present online discussion forum semantics. We hypothesize that the semantic modeling through analytics on open online discussion forums can help users examine the post content by viewing the summarized topic facets. Our preliminary results demonstrated that TFM can be a promising method to extract topic specificity from conversational and relatively short texts in online programming discussion forums.",
keywords = "Automated Assessment, Discourse Analytics, Discussion Forums, LDA, Learning Analytics, Programming, SLDA, TFM, Topic Modeling",
author = "Ihan Hsiao and Piyush Awasthi",
note = "Copyright: Copyright 2016 Elsevier B.V., All rights reserved.; 5th International Conference on Learning Analytics and Knowledge, LAK 2015 ; Conference date: 16-03-2015 Through 20-03-2015",
year = "2015",
month = mar,
day = "16",
doi = "10.1145/2723576.2723613",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "231--235",
booktitle = "Proceedings of the 5th International Conference on Learning Analytics and Knowledge, LAK 2015",
}