CAPER:以情报为目的抓取和分析Facebook

C. Aliprandi, Antonio Ercole De Luca, Giulia Di Pietro, Matteo Raffaelli, Davide Gazzè, M. L. Polla, Andrea Marchetti, M. Tesconi
{"title":"CAPER:以情报为目的抓取和分析Facebook","authors":"C. Aliprandi, Antonio Ercole De Luca, Giulia Di Pietro, Matteo Raffaelli, Davide Gazzè, M. L. Polla, Andrea Marchetti, M. Tesconi","doi":"10.1109/ASONAM.2014.6921656","DOIUrl":null,"url":null,"abstract":"Organised crime uses information technology systems to communicate, work or expand its influence. The EU FP7 Security Research Project CAPER (Collaborative information, Acquisition, Processing, Exploitation and Reporting for the prevention of organised crime), created in cooperation with European Law Enforcement Agencies (LEAs), aims to build a common collaborative and information sharing platform for the detection and prevention of organised crime, which exploits Open Source Intelligence (OSINT). LEAs are becoming more inclined to using OSINT tools, and particularly tools able to manage Online Social Networks (OSNs) data. This paper presents the CAPER Facebook crawling and analysis subsystem. Heuristic algorithms have been implemented in order to extract specific properties of Facebook's social graph, in particular user interactions. To support analysis tasks specifically, extensive effort has been spent on the analysis of textual user generated content and on the recognition of named-entities, in particular person names, locations and organisations. Relationships between users and entities mentioned in posts and in related comments are created and merged into the users networks extracted from the social graph. All entity relationships are finally visualised in user-friendly network graphs.","PeriodicalId":143584,"journal":{"name":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"CAPER: Crawling and analysing Facebook for intelligence purposes\",\"authors\":\"C. Aliprandi, Antonio Ercole De Luca, Giulia Di Pietro, Matteo Raffaelli, Davide Gazzè, M. L. Polla, Andrea Marchetti, M. Tesconi\",\"doi\":\"10.1109/ASONAM.2014.6921656\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Organised crime uses information technology systems to communicate, work or expand its influence. The EU FP7 Security Research Project CAPER (Collaborative information, Acquisition, Processing, Exploitation and Reporting for the prevention of organised crime), created in cooperation with European Law Enforcement Agencies (LEAs), aims to build a common collaborative and information sharing platform for the detection and prevention of organised crime, which exploits Open Source Intelligence (OSINT). LEAs are becoming more inclined to using OSINT tools, and particularly tools able to manage Online Social Networks (OSNs) data. This paper presents the CAPER Facebook crawling and analysis subsystem. Heuristic algorithms have been implemented in order to extract specific properties of Facebook's social graph, in particular user interactions. To support analysis tasks specifically, extensive effort has been spent on the analysis of textual user generated content and on the recognition of named-entities, in particular person names, locations and organisations. Relationships between users and entities mentioned in posts and in related comments are created and merged into the users networks extracted from the social graph. All entity relationships are finally visualised in user-friendly network graphs.\",\"PeriodicalId\":143584,\"journal\":{\"name\":\"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)\",\"volume\":\"122 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASONAM.2014.6921656\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASONAM.2014.6921656","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

有组织犯罪利用信息技术系统进行交流、工作或扩大其影响力。欧盟FP7安全研究项目CAPER(预防有组织犯罪的协同信息、获取、处理、利用和报告)是与欧洲执法机构(LEAs)合作创建的,旨在建立一个共同的协作和信息共享平台,用于探测和预防利用开源情报(OSINT)的有组织犯罪。LEAs越来越倾向于使用OSINT工具,特别是能够管理在线社交网络(Online Social Networks, osn)数据的工具。本文介绍了CAPER Facebook爬虫和分析子系统。启发式算法已经实现,以便提取Facebook社交图谱的特定属性,特别是用户交互。为了支持具体的分析任务,在文本用户生成内容的分析和命名实体的识别上花费了大量的精力,特别是人名、地点和组织。用户与帖子和相关评论中提到的实体之间的关系被创建并合并到从社交图中提取的用户网络中。所有的实体关系最终在用户友好的网络图中可视化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CAPER: Crawling and analysing Facebook for intelligence purposes
Organised crime uses information technology systems to communicate, work or expand its influence. The EU FP7 Security Research Project CAPER (Collaborative information, Acquisition, Processing, Exploitation and Reporting for the prevention of organised crime), created in cooperation with European Law Enforcement Agencies (LEAs), aims to build a common collaborative and information sharing platform for the detection and prevention of organised crime, which exploits Open Source Intelligence (OSINT). LEAs are becoming more inclined to using OSINT tools, and particularly tools able to manage Online Social Networks (OSNs) data. This paper presents the CAPER Facebook crawling and analysis subsystem. Heuristic algorithms have been implemented in order to extract specific properties of Facebook's social graph, in particular user interactions. To support analysis tasks specifically, extensive effort has been spent on the analysis of textual user generated content and on the recognition of named-entities, in particular person names, locations and organisations. Relationships between users and entities mentioned in posts and in related comments are created and merged into the users networks extracted from the social graph. All entity relationships are finally visualised in user-friendly network graphs.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信