Conformance Evaluation of Topic Modeling Approaches on Web Based Short Text Dynamic Graph Databases

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Taherparvar Mohadeseh; ahmadi Abkenari Fatemeh; BAYAT PEYMAN

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2021 | Issue:7

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Title

Conformance Evaluation of Topic Modeling Approaches on Web Based Short Text Dynamic Graph Databases

Author(s)

Taherparvar Mohadeseh | ahmadi Abkenari Fatemeh | BAYAT PEYMAN

Keywords

Community detection

Content analysis

Machine learning

Text mining

Topic modeling

Abstract

Topic modeling is a popular analytical approach for extracting topics from textual data and clustering them. There are many methods for Topic modeling that consider the types of relationships and constraints for different types of datasets. Many researchers have been interested in Dirichlet's Latent Analysis (LDA) modeling method because of its flexibility and compatibility. But choosing this method on complex and dynamic datasets brings many challenges. Due to the rapid development of social networks and the existence of dynamic and short text databases, the aim of this research is to investigate the feasibility of using the best Topic modeling appeoach based on evaluation criteria such as topic coherence, runtime, exclusivity and perplexity. In this paper, various approaches for Topic modeling on dynamic short text datasets are analyzed. Such datasets can have a variety of applications. Article-related datasets, social media datasets and user feedback databases about a product offered by a business are among them. Due to the graph-based nature of the dataset used in this study (DBLP dataset), the results obtained from our experiments, helps a lot in the challenging problem of identifying communities in the field of graph analysis. Proper identification of communities can be effective in finding appropriate influential nodes in research areas based on customer based graph analysis such as viral marketing. The results of employing various Topic modeling methods on the DBLP database and the node type of article title and the evaluation of the results with the mentioned topic evaluation criteria show the stability and compatibility of the Biterm method on this database.

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APA: Copy

Taherparvar, Mohadeseh, ahmadi Abkenari, Fatemeh, & BAYAT, PEYMAN. (2021). Conformance Evaluation of Topic Modeling Approaches on Web Based Short Text Dynamic Graph Databases. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/949455/en

Vancouver: Copy

Taherparvar Mohadeseh, ahmadi Abkenari Fatemeh, BAYAT PEYMAN. Conformance Evaluation of Topic Modeling Approaches on Web Based Short Text Dynamic Graph Databases. 2021. Available from: https://sid.ir/paper/949455/en

IEEE: Copy

Mohadeseh Taherparvar, Fatemeh ahmadi Abkenari, and PEYMAN BAYAT, “Conformance Evaluation of Topic Modeling Approaches on Web Based Short Text Dynamic Graph Databases,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2021, [Online]. Available: https://sid.ir/paper/949455/en

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