Abstract
In today’s era, online social communities such as Q&A sites are widely used for asking favors, so it would be beneficial to formulate a technique that would help in predicting the success of the response. The objective of the paper is to enhance the accuracy of prediction of the success of altruistic request that follows the same approach as used by ADJ (Proceedings of AAAI International Conference on Web and Social Media, ICWSM, 2014 [1]. Three more features are proposed, i.e., topic, role, and centrality in addition to the features proposed by ADJ [1]) to capture user’s interaction in the past and topic effect on the prediction of response. We also propose a graph-based success prediction (GSP) model that uses feature weights and uses the underlying graph structure for the propagation to predict the outcome of a request. Experiments were conducted on the RAOP dataset which belongs to sub-community of Reddit.com using GSP, and it outperformed ADJ and other baseline methods using limited training data.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Althoff, T., Danescu-Niculescu-Mizil, C., Jurafsky, D. (ADJ): How to ask for a favor: a case study on the success of altruistic request. In: Proceedings of AAAI International Conference on Web and Social Media, ICWSM (2014)
Backstrom, L., Huttenlocher, D., Kleinberg, J., Lan, X.: Group formation in large social networks: membership, growth, and evolution. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD, pp. 44–54 (2006)
Freedman, D.A.: Statistical Models: Theory and Practice, pp. 128 (Cambridge University Press, 2009)
Scripps, J., Tan, P.N., Esfahanian, A.H.: Exploration of link structure and community-based node roles in network analysis. In: Proceedings of the IEEE International Conference on Data Mining, ICDM, pp. 649–654 (2007)
Ugander, J., Backstrom, L., Marlow, C., Kleinberg, J.: Structural diversity in social contagion. Proc. Nat. Acad. Sci. U.S.A. (PNAS) 109(16), 5962–5966 (2012)
Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273297 (1995)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Ahmad, A., Ahmad, T., Bhatt, A. (2019). A Novel Approach for Predicting the Outcome of Request in RAOP Dataset. In: Jain, L., E. Balas, V., Johri, P. (eds) Data and Communication Networks. Advances in Intelligent Systems and Computing, vol 847. Springer, Singapore. https://doi.org/10.1007/978-981-13-2254-9_20
Download citation
DOI: https://doi.org/10.1007/978-981-13-2254-9_20
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-2253-2
Online ISBN: 978-981-13-2254-9
eBook Packages: EngineeringEngineering (R0)