Analysis of the Impact of Tags on Stack Overflow Questions

ECU Author/Contributor (non-ECU co-authors, if there are any, appear on document)

Von Kendall Ithipathachai (Creator)

Institution

East Carolina University (ECU )

Web Site: http://www.ecu.edu/lib/

Abstract: User queries on Stack Overflow commonly suffer from either inadequate length or inadequate\nclarity with regards to the languages and/or tools they are meant for. Although the site makes use\nof a tagging system for classifying questions, tags are used minimally (if at all). To investigate the\nimpact of tags in the quality of results returned by the queries, in this research we propose a new\nquery expansion solution. Our technique assigns tags to queries based on how well they match the\nqueries’ topics. We evaluated our technique on eight sets of queries categorized by overall length\nand programming language. We examined the retrieval results by adding varying numbers of tags\nto the queries, and monitored the recall and precision rates. Our results indicate that queries yield\nconsiderably higher recall and precision rates with extra tags than without. We further conclude\nthat tags are a particularly effective means of enhancement when the original queries do not already\nreturn sufficient yields to begin with.

Additional Information

Publication

Thesis

Language: English

Date: 2023

Subjects

StackOverflow Analysis;Topic Modeling;Tag Recommendation;Query Reformulation

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