On cost-aware biased respondent group selection for minority opinion survey

This paper discusses a new approach to use a specially constructed social relation graph with high homophily to select a survey respondent group under a limited budget such that the result of the survey is biased to the minority opinions. This approach has a wide range of potential applications, e.g., collecting diversified complaints from the customers while most of them are satisfied, but is hardly investigated. We formulate the problem of computing such a group as the p-biased-representative selection problem (p-BRSP), where p represents the size of the group constraint by the available budget. This problem has two independent optimization goals and therefore is difficult to deal with. We introduce two polynomial time algorithms for the problem, where each of which has an approximation ratio with respect to each of the objectives when the other optimization objective is substituted with a constraint. Under the substituted constraint, we prove that the first algorithm is an O(lnΔ)-approximation (which i...

[1]  A. Frieze,et al.  A simple heuristic for the p-centre problem , 1985 .

[2]  Nitin Agarwal,et al.  A study of homophily on social media , 2012, World Wide Web.

[3]  Konstantin Beznosov,et al.  A study on the influential neighbors to maximize information diffusion in online social networks , 2015 .

[4]  Eleanor Singer,et al.  The Use and Effects of Incentives in Surveys , 2013 .

[5]  Mario Ventresca,et al.  Efficiently identifying critical nodes in large complex networks , 2015 .

[6]  Petr Slavík Improved Performance of the Greedy Algorithm for Partial Cover , 1997, Inf. Process. Lett..

[7]  Donghyun Kim,et al.  Biased Respondent Group Selection Under Limited Budget for Minority Opinion Survey , 2015, CSoNet.

[8]  Donghyun Kim,et al.  Efficient respondents selection for biased survey using homophily-high social relation graph , 2016, Discret. Math. Algorithms Appl..

[9]  David B. Shmoys,et al.  A Best Possible Heuristic for the k-Center Problem , 1985, Math. Oper. Res..

[10]  Chunyu Ai,et al.  A partner-matching framework for social activity communities , 2014 .

[11]  Weili Wu,et al.  Efficient influence spread estimation for influence maximization under the linear threshold model , 2014, Computational Social Networks.

[12]  Vasja Vehovar,et al.  Overview: Online Surveys , 2008 .

[13]  Vasileios Karyotis,et al.  Exploiting social features for improving cognitive radio infrastructures and social services via combined MRF and back pressure cross-layer resource allocation , 2014, Computational Social Networks.

[14]  B. Duffy,et al.  Comparing Data from Online and Face-to-face Surveys , 2005 .