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A typical approach to detect fraud activity has been to analyze registered user profiles, user\u2019s behavior, and texts attached to individual transactions and the user. However, this traditional approach may be limited because malicious users can easily conceal their information. Given this background, network indices have been exploited for detecting frauds in various online transaction platforms. In the present study, we analyzed networks of users of an online consumer-to-consumer marketplace in which a seller and the corresponding buyer of a transaction are connected by a directed edge. We constructed egocentric networks of each of several hundreds of fraudulent users and those of a similar number of normal users. We calculated eight local network indices based on up to connectivity between the neighbors of the focal node. Based on the present descriptive analysis of these network indices, we fed twelve features that we constructed from the eight network indices to random forest classifiers with the aim of distinguishing between normal users and fraudulent users engaged in each one of the four types of problematic transactions. We found that the classifier accurately distinguished the fraudulent users from normal users and that the classification performance did not depend on the type of problematic transaction.<\/jats:p>","DOI":"10.1007\/s41109-020-00330-x","type":"journal-article","created":{"date-parts":[[2020,11,16]],"date-time":"2020-11-16T10:06:18Z","timestamp":1605521178000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Detecting problematic transactions in a consumer-to-consumer e-commerce network"],"prefix":"10.1007","volume":"5","author":[{"given":"Shun","family":"Kodate","sequence":"first","affiliation":[]},{"given":"Ryusuke","family":"Chiba","sequence":"additional","affiliation":[]},{"given":"Shunya","family":"Kimura","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1567-801X","authenticated-orcid":false,"given":"Naoki","family":"Masuda","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,11,16]]},"reference":[{"key":"330_CR1","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.jnca.2016.04.007","volume":"68","author":"A Abdallah","year":"2016","unstructured":"Abdallah A, Maarof MA, Zainal A (2016) Fraud detection system: a survey. 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However, this fact does not cause any conflict of interest because the analyses, results and their interpretation are free of any bias towards the merit of the company.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"90"}}