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Provenance data in social media / Geoffrey Barbier Air Force Research Laboratory, [and three others].

By: Contributor(s): Series: Synthesis lectures on data mining and knowledge discovery ; #7.Publisher: [San Rafael, California] : Morgan & Claypool Publishers, [2013]Copyright date: © 2013Description: xi, 72 pages : illustrations, 24 cmContent type:
  • text
  • still image
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781608457830
  • 1608457834
Subject(s): Abstract: '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 judgments about statements published in social media.'--Page [vi].
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Item type Current library Home library Call number Materials specified Copy number Status Date due Barcode
AM PERPUSTAKAAN LINGKUNGAN KEDUA PERPUSTAKAAN LINGKUNGAN KEDUA KOLEKSI AM-P. LINGKUNGAN KEDUA HM742.B347 3 (Browse shelf(Opens below)) 1 Available 00002153501

Printed version of a work that appears in: Synthesis digital library of engineering and computer science.

Includes bibliographical references : (p. 65-70).

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

'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 judgments about statements published in social media.'--Page [vi].

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