The Information Ecology of Social Media and Online Communities

被引：32

作者：

Finin, Tim ^{[1
,2
,3
]}

Joshi, Anupam ^{[1
]}

Kolari, Pranam

Java, Akshay ^{[1
]}

Kale, Anubhav ^{[1
]}

Karandikar, Amit ^{[1
]}

机构：

[1] Univ Maryland Baltimore Cty, Baltimore, MD 21228 USA

[2] Univ Penn, Philadelphia, PA 19104 USA

[3] MIT, AI Lab, Cambridge, MA 02139 USA

来源：

AI MAGAZINE | 2008年 / 29卷 / 03期

基金：

美国国家科学基金会;

关键词：

D O I：

10.1609/aimag.v29i3.2158

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Social media systems such as weblogs, photo- and link-sharing sites, wikis, and online forums are currently thought to produce up to one third of new web content One thing that sets these "web 2.0" sites apart from traditional web pages and resources is that they are intertwined with other forms of networked data. Their standard hyperlinks are enriched by social networks, comments, trackbacks, advertisements, tags, RDF data, and metadata. We describe recent work on building systems that use models of the blogosphere to recognize spam blogs, find opinions on topics, identify communities of interest, derive trust relationships, and detect influential bloggers.

引用

页码：77 / 92

页数：16

共 23 条

[1]

Adamic L., 2005, P 3 INT WORKSH LINK

[2]

[Anonymous], THESIS U MARYLAND BA

[3]

BALIJEPALLI S, 2007, THESIS U MARYLAND BA

[4] Emergence of scaling in random networks [J].

Barabási, AL ;

Albert, R .

SCIENCE, 1999, 286 (5439) :509-512

[5]

Boser B. E., 1992, Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory, P144, DOI 10.1145/130385.130401

[6]

Chung F., 2006, CBMS REGIONAL C SERI, DOI 10.1090/cbms/107

[7]

Gibson D., 1998, PROC HYPERTEXT, P225, DOI DOI 10.1145/276627.276652

[8]

Guha R., 2004, P 13 INT C WORLD WID, P403, DOI [DOI 10.1145/988672.988727, 10.1145/988672.988727]

[9]

JAVA A, 2007, P 2 INT C WEB LOGS S

[10]

JAVA A, 2007, P 15 TEXT RETR C WAS

← 1 2 3 →