Ralf Krestel

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NLDB 16

Topic Shifts in StackOverflow: Ask it like Socrates

Abstract

Community based question-and-answer (Q&A) sites rely on well posed and appropriately tagged questions. However, most platforms have only limited capabilities to support their users in finding the right tags. In this paper, we propose a temporal recommendation model to support users in tagging new questions and thus improve their acceptance in the community. To underline the necessity of temporal awareness of such a model, we first investigate the changes in tag usage and show different types of collective attention in StackOverflow, a community-driven Q&A website for computer programming topics. Furthermore, we examine the changes over time in the correlation between question terms and topics. Our results show that temporal awareness is indeed important for recommending tags in Q&A communities.

Full Paper

NLDB16.pdf

Conference Homepage

NLDB 2016

BibTex Entry

@InProceedings{krestel-nldb16, author = {Toni Gruetze and Ralf Krestel and Felix Naumann}, title = {Topic Shifts in StackOverflow: Ask it like Socrates}, booktitle = {Natural Language Processing and Information Systems --- 21st International Conference on Applications of Natural Language to Information Systems (NLDB), Proceedings}, pages = {213--221}, location = {Manchester, UK}, month = {June 22--24}, year = {2016}, series = {Lecture Notes in Computer Science}, volume = {9612}, isbn = {978-3-319-41754-7}, publisher = {Springer} }