Identifying Trends in Technologies and Programming Languages Using Topic Modeling

Vishal Johri, Srividya Bansal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Technology question and answer websites are a great source of technical knowledge. Users of these websites raise various types of technical questions, and answer them. These questions cover a wide range of domains in Computer Science like Networks, Data Mining, Multimedia, Multi-threading, Web Development, Mobile App Development, etc. Analyzing the actual textual content of these websites can help computer science and software engineering community better understand the needs of developers and learn about the current trends in technology. In this project, textual data from famous question and answer website called StackOverflow, is analyzed using Latent Dirichlet Allocation (LDA) topic modeling algorithm. The results show that this techniques help discover dominant topics in developer discussions. These topics are analyzed to find a number of interesting observations such as popular technology/language, impact of a technology, technology trends over time, relationship of a technology/language with other technologies and comparison of technologies addressing an area of computer science or software engineering.

Original languageEnglish (US)
Title of host publicationProceedings - 12th IEEE International Conference on Semantic Computing, ICSC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages391-396
Number of pages6
Volume2018-January
ISBN (Electronic)9781538644072
DOIs
Publication statusPublished - Apr 9 2018
Event12th IEEE International Conference on Semantic Computing, ICSC 2018 - Laguna Hills, United States
Duration: Jan 31 2018Feb 2 2018

Other

Other12th IEEE International Conference on Semantic Computing, ICSC 2018
CountryUnited States
CityLaguna Hills
Period1/31/182/2/18

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Keywords

  • Latent Dirichlet Allocation (LDA)
  • Machine Learning
  • Natural Language Processing
  • Topic modeling

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Information Systems and Management

Cite this

Johri, V., & Bansal, S. (2018). Identifying Trends in Technologies and Programming Languages Using Topic Modeling. In Proceedings - 12th IEEE International Conference on Semantic Computing, ICSC 2018 (Vol. 2018-January, pp. 391-396). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSC.2018.00078