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Developers' information seeking in Question & Answer websites through a gender lens

Abim Sedhain, Vaishvi Diwanji, Helen Solomon,Shahnewaz Leon,Sandeep Kaur Kuttal

JOURNAL OF COMPUTER LANGUAGES(2024)

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Abstract
Question & Answer websites for developers, such as Stack Overflow, contain enormous programming knowledge which can be redundant and cost substantial time and cognitive effort. We investigated the information seeking behavior of developers on Stack Overflow using Information Foraging Theory. To understand the influence of gender on foraging patterns, we conducted a gender-balanced think-aloud lab study with 12 participants, followed by retrospective interviews. The participants performed two debugging tasks: (1) understand foraging between question variants and (2) understand foraging between answer variants, on Stack Overflow. Various cues and strategies were utilized by the participants to find relevant question and optimal answer on Stack Overflow. The effect of gender on their foraging pattern was observed as male participants used 19.7% more cues and spent 55% more time than female participants. We also categorized various cues in terms of cost-value proposition and reported a debugging foraging model for Stack Overflow. Our study has implications for Question and Answer websites as well as Information Foraging Theory.
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Key words
Information Foraging Theory,Stack Overflow,Question & Answer websites,Gender,Qualitative analysis
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