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More than 80 civic tech communities in Japan are developing informationtechnology (IT) systems to solve their regional issues. Collaboration amongsuch communities across different regions assists in solving their problemsbecause some groups have limited IT knowledge and experience for this purpose.Our objective is to realize a civic tech matchmaking system to assist suchcommunities in finding better partners with IT experience in their issues. Inthis study, as the first step toward collaboration, we acquire relevant socialissues and information technologies by association rule mining. To meet ourchallenge, we supply a questionnaire to members of civic tech communities andobtain answers on their faced issues and their available technologies.Subsequently, we match the relevant issues and technologies from the answers.However, most of the issues and technologies in this questionnaire data areinfrequent, and there is a significant bias in their occurrence. Here, it isdifficult to extract truly relevant issues--technologies combinations withexisting interestingness measures. Therefore, we introduce a new measure calledweighted casual confidence, and show that our measure is effective for miningrelevant issues--technologies pairs.

Matching Social Issues to Technologies for Civic Tech by Association Rule Mining using Weighted Casual Confidence