Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (p. 65-70).

1. Information provenance in social media -- 1.1 Social media -- 1.2 Social media data -- 1.3 Information provenance -- 1.4 The information provenance problem -- 1.5 Challenges -- 1.6 In search of provenance data -- 1.6.1 Analyzing provenance attributes -- 1.6.2 Seeking provenance via network information -- 1.6.3 Searching for provenance data -- 1.7 Summary --

2. Provenance attributes -- 2.1 Defining provenance attributes -- 2.2 Measuring provenance attributes -- 2.3 Analyzing provenance attributes -- 2.4 Summary --

3. Provenance via network information -- 3.1 Information propagation models -- 3.1.1 Susceptible-infected (SI) model -- 3.1.2 Independent-cascade (IC) model -- 3.2 Seeking provenance of information -- 3.2.1 Directly seeking sources when all recipients are known -- 3.2.2 Finding provenance paths when a few recipients are known -- 3.3 Key issues in information provenance -- 3.4 Summary --

4. Provenance data -- 4.1 An iterative framework -- 4.2 Propagation history -- 4.2.1 Feature extraction -- 4.2.2 Ranking measures -- 4.2.3 Follower-ranking prediction methods -- 4.3 A case study of disinformation in Assam Exodus -- 4.4 Summary --

A. Notations -- B. Online provenance data tool -- Bibliography -- Authors' biography.

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

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Social media shatters the barrier to communicate anytime anywhere for people of all walks of life. The publicly available, virtually free information in social media poses a new challenge to consumers who have to discern whether a piece of information published in social media is reliable. For example, it can be difficult to understand the motivations behind a statement passed from one user to another, without knowing the person who originated the message. Additionally, false information can be propagated through social media, resulting in embarrassment or irreversible damages. Provenance data associated with a social media statement can help dispel rumors, clarify opinions, and confirm facts. However, provenance data about social media statements is not readily available to users today. Currently, providing this data to users requires changing the social media infrastructure or offering subscription services. Taking advantage of social media features, research in this nascent field spearheads the search for a way to provide provenance data to social media users, thus leveraging social media itself by mining it for the provenance data. Searching for provenance data reveals an interesting problem space requiring the development and application of new metrics in order to provide meaningful provenance data to social media users. This lecture reviews the current research on information provenance, explores exciting research opportunities to address pressing needs, and shows how data mining can enable a social media user to make informed judgements about statements published in social media.

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Title from PDF t.p. (viewed on June 15, 2013).