2020/08/31 by Takeshi Kato, Yasuhiro Asa, Misa Owa
Computer Science · Decision Sciences · Economics, Econometrics and Finance · Physics and Astronomy · #Aggregate (composite) #Data aggregator #Distribution (mathematics) #Game Theory and Voting Systems #Majority rule #Multi-Criteria Decision Making #Opinion Dynamics and Social Influence #Position (finance) #Ranking (information retrieval) #Social choice theory #Voting #Weighting #acm:91F99 #cs.CY #econ.GN #msc:91F99 #physics.soc-ph #q-fin.EC
paper · pdf · doi:10.11114/ijsss.v9i2.5171
published as International Journal of Social Science Studies, Vol. 9, No. 2 (2021) 79-88 · 10 pages, 3 figures. Published online at http://www.redfame.com/journal/index.php/ijsss/article/view/5171
openalex created_date 2020/08/24 · arxiv created 2021/02/23 · openalex publication_date 2021/02/23 · arxiv updated 2021/02/24 · openalex updated_date 2026/08/05
Respecting minority opinions is vital in solving social problems. However, minority opinions are often ignored in general majority rules. To build consensus on pluralistic values and make social choices that consider minority opinions, we propose aggregation methods that give weighting to the minority's positionality on cardinal cumulative voting. Based on quadratic and linear voting, we formulated three weighted aggregation methods that differ in the ratio of votes to cumulative points and the weighting of the minority to all members, and assuming that the distributions of votes follow normal distributions, we calculated the frequency distributions of the aggregation results. We found that minority opinions are more likely to be reflected proportionately to the average of the distribution in two of the above three methods. This implies that Sen and Gotoh's idea of considering the social position of unfortunate people on ordinal ranking in the welfare economics, was illustrated by weighting the minority's positionality on cardinal voting. In addition, it is possible to visualize the number and positionality of the minority from the analysis of the aggregation results. These results will be useful to promote mutual understanding between the majority and minority by interactively visualizing the contents of the proposed aggregation methods in the consensus-building process. With the further development of information technology, the consensus building based on big data will be necessary. We recommend the use of our proposed aggregation methods to make social choices for pluralistic values such as social, environmental, and economic.