面向在线社交网络用户行为建模的详尽框架

Alessia Antelmi
{"title":"面向在线社交网络用户行为建模的详尽框架","authors":"Alessia Antelmi","doi":"10.1145/3320435.3323466","DOIUrl":null,"url":null,"abstract":"Since the advent of Web 2.0, Online Social Networks (OSNs) represent a rich opportunity for researchers to collect real user data and to explore OSNs user behaviour. Based on the current challenges and future directions proposed in literature, we aim to investigate how to comprehensively model OSNs user behaviours, by exploiting and combining user data of different nature. We propose to use hypergraphs as a model to easily analyse and combine structural, semantic, and activity-related user information, and to study their evolution over time. This novel user behaviour modelling technique will converge in open, efficient, and scalable libraries, which will be integrated into a modular framework able to handle the data crawling process from several OSNs.","PeriodicalId":254537,"journal":{"name":"Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Towards an Exhaustive Framework for Online Social Networks User Behaviour Modelling\",\"authors\":\"Alessia Antelmi\",\"doi\":\"10.1145/3320435.3323466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Since the advent of Web 2.0, Online Social Networks (OSNs) represent a rich opportunity for researchers to collect real user data and to explore OSNs user behaviour. Based on the current challenges and future directions proposed in literature, we aim to investigate how to comprehensively model OSNs user behaviours, by exploiting and combining user data of different nature. We propose to use hypergraphs as a model to easily analyse and combine structural, semantic, and activity-related user information, and to study their evolution over time. This novel user behaviour modelling technique will converge in open, efficient, and scalable libraries, which will be integrated into a modular framework able to handle the data crawling process from several OSNs.\",\"PeriodicalId\":254537,\"journal\":{\"name\":\"Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3320435.3323466\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3320435.3323466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

自Web 2.0出现以来,在线社交网络为研究人员提供了收集真实用户数据和探索社交网络用户行为的丰富机会。基于当前的挑战和文献提出的未来方向,我们的目标是研究如何通过利用和结合不同性质的用户数据来全面建模osn用户行为。我们建议使用超图作为模型来轻松地分析和组合结构、语义和与活动相关的用户信息,并研究它们随时间的演变。这种新颖的用户行为建模技术将融合在开放、高效和可扩展的库中,这些库将集成到一个模块化框架中,能够处理来自多个osn的数据爬行过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Towards an Exhaustive Framework for Online Social Networks User Behaviour Modelling
Since the advent of Web 2.0, Online Social Networks (OSNs) represent a rich opportunity for researchers to collect real user data and to explore OSNs user behaviour. Based on the current challenges and future directions proposed in literature, we aim to investigate how to comprehensively model OSNs user behaviours, by exploiting and combining user data of different nature. We propose to use hypergraphs as a model to easily analyse and combine structural, semantic, and activity-related user information, and to study their evolution over time. This novel user behaviour modelling technique will converge in open, efficient, and scalable libraries, which will be integrated into a modular framework able to handle the data crawling process from several OSNs.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Adaptive Modelling of Attentiveness to Messaging: A Hybrid Approach Engagement, Metrics and Personalisation: the Good, the Bad and the Ugly Towards Social Choice-based Explanations in Group Recommender Systems Personalized Gait-based Authentication Using UWB Wearable Devices Towards Utter Well-Being: Personalization for Guardian Angels
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1