{"title":"社区学习:优秀用户与其他用户有何不同?","authors":"T. B. Procaci, S. Siqueira, B. Nunes","doi":"10.1109/ICALT.2018.00048","DOIUrl":null,"url":null,"abstract":"This paper reports on an investigation into outstanding and ordinary users of two Question & Answer (Q&A) communities. Considering some learning-related perspectives such as participation, linguistic traits, social ties, influence, and focus, we found that outstanding users are (i) more likely to engage in discussions; (ii) they tend to use more sophisticated linguistic traits; (iii) their inclusion into a discussion results in longer debates; (iv) they value the diversity of their connections; (v) they participate in several topics, rather than one specialist niche. These findings allow us to use behavioral patterns to predict whether a given user is outstanding and also predict which answer gives a definitive solution for a question.","PeriodicalId":361110,"journal":{"name":"2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)","volume":"285 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Learning in Communities: How Do Outstanding Users Differ From Other Users?\",\"authors\":\"T. B. Procaci, S. Siqueira, B. Nunes\",\"doi\":\"10.1109/ICALT.2018.00048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper reports on an investigation into outstanding and ordinary users of two Question & Answer (Q&A) communities. Considering some learning-related perspectives such as participation, linguistic traits, social ties, influence, and focus, we found that outstanding users are (i) more likely to engage in discussions; (ii) they tend to use more sophisticated linguistic traits; (iii) their inclusion into a discussion results in longer debates; (iv) they value the diversity of their connections; (v) they participate in several topics, rather than one specialist niche. These findings allow us to use behavioral patterns to predict whether a given user is outstanding and also predict which answer gives a definitive solution for a question.\",\"PeriodicalId\":361110,\"journal\":{\"name\":\"2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)\",\"volume\":\"285 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICALT.2018.00048\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICALT.2018.00048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Learning in Communities: How Do Outstanding Users Differ From Other Users?
This paper reports on an investigation into outstanding and ordinary users of two Question & Answer (Q&A) communities. Considering some learning-related perspectives such as participation, linguistic traits, social ties, influence, and focus, we found that outstanding users are (i) more likely to engage in discussions; (ii) they tend to use more sophisticated linguistic traits; (iii) their inclusion into a discussion results in longer debates; (iv) they value the diversity of their connections; (v) they participate in several topics, rather than one specialist niche. These findings allow us to use behavioral patterns to predict whether a given user is outstanding and also predict which answer gives a definitive solution for a question.