What are developers talking about? An analysis of topics and trends in Stack Overflow.
Saved in:
| Title: | What are developers talking about? An analysis of topics and trends in Stack Overflow. |
|---|---|
| Authors: | Barua, Anton1 barua@cs.queensu.ca, Thomas, Stephen1 sthomas@cs.queensu.ca, Hassan, Ahmed1 ahmed@cs.queensu.ca |
| Source: | Empirical Software Engineering. Jun2014, Vol. 19 Issue 3, p619-654. 36p. |
| Subjects: | Stack Overflow (Company), Prolog (Computer program language), Trend analysis, Web development, Mobile apps, Software engineering, Computer network resources |
| Abstract: | Programming question and answer (Q&A) websites, such as Stack Overflow, leverage the knowledge and expertise of users to provide answers to technical questions. Over time, these websites turn into repositories of software engineering knowledge. Such knowledge repositories can be invaluable for gaining insight into the use of specific technologies and the trends of developer discussions. Previous work has focused on analyzing the user activities or the social interactions in Q&A websites. However, analyzing the actual textual content of these websites can help the software engineering community to better understand the thoughts and needs of developers. In the article, we present a methodology to analyze the textual content of Stack Overflow discussions. We use latent Dirichlet allocation (LDA), a statistical topic modeling technique, to automatically discover the main topics present in developer discussions. We analyze these discovered topics, as well as their relationships and trends over time, to gain insights into the development community. Our analysis allows us to make a number of interesting observations, including: the topics of interest to developers range widely from jobs to version control systems to C# syntax; questions in some topics lead to discussions in other topics; and the topics gaining the most popularity over time are web development (especially jQuery), mobile applications (especially Android), Git, and MySQL. [ABSTRACT FROM AUTHOR] |
| Copyright of Empirical Software Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 95594077 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: What are developers talking about? An analysis of topics and trends in Stack Overflow. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Barua%2C+Anton%22">Barua, Anton</searchLink><relatesTo>1</relatesTo><i> barua@cs.queensu.ca</i><br /><searchLink fieldCode="AR" term="%22Thomas%2C+Stephen%22">Thomas, Stephen</searchLink><relatesTo>1</relatesTo><i> sthomas@cs.queensu.ca</i><br /><searchLink fieldCode="AR" term="%22Hassan%2C+Ahmed%22">Hassan, Ahmed</searchLink><relatesTo>1</relatesTo><i> ahmed@cs.queensu.ca</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Empirical+Software+Engineering%22">Empirical Software Engineering</searchLink>. Jun2014, Vol. 19 Issue 3, p619-654. 36p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Stack+Overflow+%28Company%29%22">Stack Overflow (Company)</searchLink><br /><searchLink fieldCode="DE" term="%22Prolog+%28Computer+program+language%29%22">Prolog (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Trend+analysis%22">Trend analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Web+development%22">Web development</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+apps%22">Mobile apps</searchLink><br /><searchLink fieldCode="DE" term="%22Software+engineering%22">Software engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+network+resources%22">Computer network resources</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Programming question and answer (Q&A) websites, such as Stack Overflow, leverage the knowledge and expertise of users to provide answers to technical questions. Over time, these websites turn into repositories of software engineering knowledge. Such knowledge repositories can be invaluable for gaining insight into the use of specific technologies and the trends of developer discussions. Previous work has focused on analyzing the user activities or the social interactions in Q&A websites. However, analyzing the actual textual content of these websites can help the software engineering community to better understand the thoughts and needs of developers. In the article, we present a methodology to analyze the textual content of Stack Overflow discussions. We use latent Dirichlet allocation (LDA), a statistical topic modeling technique, to automatically discover the main topics present in developer discussions. We analyze these discovered topics, as well as their relationships and trends over time, to gain insights into the development community. Our analysis allows us to make a number of interesting observations, including: the topics of interest to developers range widely from jobs to version control systems to C# syntax; questions in some topics lead to discussions in other topics; and the topics gaining the most popularity over time are web development (especially jQuery), mobile applications (especially Android), Git, and MySQL. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Empirical Software Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=95594077 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10664-012-9231-y Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 36 StartPage: 619 Subjects: – SubjectFull: Stack Overflow (Company) Type: general – SubjectFull: Prolog (Computer program language) Type: general – SubjectFull: Trend analysis Type: general – SubjectFull: Web development Type: general – SubjectFull: Mobile apps Type: general – SubjectFull: Software engineering Type: general – SubjectFull: Computer network resources Type: general Titles: – TitleFull: What are developers talking about? An analysis of topics and trends in Stack Overflow. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Barua, Anton – PersonEntity: Name: NameFull: Thomas, Stephen – PersonEntity: Name: NameFull: Hassan, Ahmed IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2014 Type: published Y: 2014 Identifiers: – Type: issn-print Value: 13823256 Numbering: – Type: volume Value: 19 – Type: issue Value: 3 Titles: – TitleFull: Empirical Software Engineering Type: main |
| ResultId | 1 |
