Abstract
Stackoverflow is one of the most popular question and answer (Q&A) websites. One of the reasons for the popularity is the use of badges and reputation score. The reputation score is cumulative of answers accepted by the community users on their posted questions on various topics. This paper tries to find out the most influential top users topic (tag) specific over a group of topics by forming social network based on the question owner and accepted user owner for a particular topic (tag) using SNAP (Stanford Network Analytics Platform). After formation of topic (tag)-specific social network graph, top 10 experts and learners are obtained using HITS algorithm. A simple scoring methodology is used to find top-n most influential experts and learners in the group of topics (tags). Three case studies are undertaken for three groups of topics (tags). We find that there are some common users appearing in the top 10 experts list in a group of topics (tags). It is also observed that there are no common users in the top 10 learners list for first two case studies. However, some users appear common in top 10 learners for more than 1 topic (tag) in the third case study which is more domain-specific. The latest Stackoverflow dataset has been used.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
M. Jackson. Social and economic networks. Princeton University Press (2008).
L. Freeman. The development of social network analysis. Empirical Press (2004).
Dana Movshovitz-Attias, Yair Movshovitz-Attias, Peter Steenkiste and Christos Faloutsos, 2013. Analysis of the reputation system and user contributions on a question answering website: Stackoverflow In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining ACM, pages 886–893.
Amiangshu Bosu, Christopher S. Corley, Dustin Heaton, DebarshiChatterji, Jeffrey C. Carver, Nicholas A. Kraft, 2013. Building reputation in Stackoverflow: an empirical investigation In Proceedings of the 10th Working Conference on Mining Software Repositories. IEEE, pages 89–92.
Clayton Stanley, Michael D. Byrne, Predicting Tags for Stackoverflow Posts, Proceedings of ICCM, 2013.
Benjamin V. Hanrahan, Gregorio Convertino, Les Nelson, Modeling problem difficulty and expertise in Stackoverflow, Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work Companion, pg. 91–94.
B. Vasilescu, A. Capiluppi, A. Serebrenik, Gender, Representation and Online Participation: A Quantitative Study of Stackoverflow, 2012 International Conference on Social Informatics (SocialInformatics), pg. 332–338.
Luca Ponzanelli, Gabriele Bavota, Massimiliano Di Penta, Rocco Oliveto, Michele Lanza. Prompter: A Self-confident Recommender System. In 30th International Conference on Software Maintenance and Evolution (ICSME’14). IEEE.
Luca Ponzanelli, Andrea Mocci, Alberto Bacchelli, Michele Lanza. 2014. Improving Low Quality Stackoverflow Post Detection. In 30th International Conference on Software Maintenance and Evolution (ICSME’14). IEEE.
N. Novielli, F. Calefato, and F. Lanubile. 2014. Towards Discovering the Role of Emotions in Stackoverflow In Proc. of the 6th International Workshop on Social Software Engineering (colocated with FSE 2014) Hong Kong, nov. 2014 ACM.
Alexander Halavais, K Hazel Kwon, Shannon Havener and Jason Striker. 2014. Badges of Friendship: Social Influence and Badge Acquisition on Stackoverflow. In 47th Hawaii International International Conference on Systems Science (HICSS-47 2014). IEEE.
Megan Squire and Christian Funkhouser. 2014. “A Bit of Code”: How the Stackoverflow Community Creates Quality Postings In 47th Hawaii International International Conference on Systems Science (HICSS-47 2014). IEEE.
Nicole Novielli, Fabio Calefato, FilippoLanubile. The Challenges of Sentiment Detection in the Social Programmer Ecosystem. In Proceedings of SSE ‘15, The 7th International Workshop on Social Software Engineering.
Fabio Calefato, FilippoLanubile, Maria ConcettaMarasciulo, Nicole Novielli. Mining Successful Answers in Stackoverflow. In Proceedings of MSR 2015, The 12th Working Conference on Mining Software Repositories.
Christoffer Rosen, EmadShihab, 2015. What are mobile developers asking about? A large scale study using Stackoverflow. In Empirical Software Engineering, April 2015.Springer Science+Business Media.
Jon M. Kleinberg, Authoritative sources in a hyperlinked environment, Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms, p. 668–677, January 25–27, 1998, San Francisco, California, USA.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Paul, S.S., Tripathi, A., Tewari, R.R. (2018). Social Influence and Learning Pattern Analysis: Case Studies in Stackoverflow. In: Bhatia, S., Mishra, K., Tiwari, S., Singh, V. (eds) Advances in Computer and Computational Sciences. Advances in Intelligent Systems and Computing, vol 554. Springer, Singapore. https://doi.org/10.1007/978-981-10-3773-3_12
Download citation
DOI: https://doi.org/10.1007/978-981-10-3773-3_12
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-3772-6
Online ISBN: 978-981-10-3773-3
eBook Packages: EngineeringEngineering (R0)