Analysis and monetization of social data
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Analysis and Monetization of Social Data. Amit P. Sheth Lexis-Nexis Ohio Eminent Scholar Director, Kno.e.sis Center , Wright State University. 222 MILLION FACEBOOK USERS. 4000000 twitter users. 52,000 F8 APPLICATIONS AND COUNTING. 3 Million tweets a day. Intents in User Activity Elsewhere.

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Analysis and Monetization of Social Data

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Analysis and monetization of social data

Analysis and Monetization of Social Data

  • Amit P. Sheth

  • Lexis-Nexis Ohio Eminent Scholar

  • Director, Kno.e.sis Center, Wright State University


Analysis and monetization of social data

222 MILLION FACEBOOK USERS

4000000 twitter users

52,000 F8 APPLICATIONS AND COUNTING

3 Million tweets a day


Intents in user activity elsewhere

Intents in User Activity Elsewhere

June 01, 2009


What why and how people write

What why and how people write

  • Cultural Entities

  • Word Usages in self-presentation

  • Slang sentiments

  • Intentions


Work and preliminary results in

Work and Preliminary Results in…

  • Identifying intents behind user posts on social networks

    • Pull UGC with most monetization potential

  • Identifying keywords for advertizing in user-generated content

    • Interpersonal communication & off-topic chatter


Identifying monetizable intents

Identifying Monetizable Intents

  • Scribe Intent not same as Web Search Intent1

  • People write sentences, not keywords or phrases

  • Presence of a keyword does not imply navigational / transactional intents

    • ‘am thinking of getting X’ (transactional)

    • ‘i like my new X’ (information sharing)

    • ‘what do you think about X’ (informationseeking)

1B. J. Jansen, D. L. Booth, and A. Spink, “Determining the informational, navigational, and transactional intent of web queries,” Inf. Process. Manage., vol. 44, no. 3, 2008.


From x to action patterns

From X to Action Patterns

  • Action patterns surrounding an entity

  • How questions are asked and not topic words that indicate what the question is about

  • “where can I find a chotto psp cam”

    • User post also has an entity


Off topic noise topical keywords

Off topic noise – topical keywords

  • Google AdSense ads for user post vs. extracted topical keywords


8x generated interest

8X Generated Interest

  • Using profile ads

    • Total of 56 ad impressions

    • 7% of ads generated interest

  • Using authored posts

    • Total of 56 ad impressions

    • 43% of ads generated interest

  • Using topical keywords from authored posts

    • Total of 59 ad impressions

    • 59% of ads generated interest


Analysis and monetization of social data

  • and then there is

  • space (where)

  • time (when)

    • theme (what)


Analysis and monetization of social data

  • twitris: spatio-temporal integration of twitter data “surrounding” an event

  • http://twitris.dooduh.com


Studying social signals

Studying social signals

  • What is new and interesting?

  • What’s a region paying attention to today? What are people most excited or concerned about?

  • Why an entity’s perception changing over time in any region?


Analysis and monetization of social data

Geocoder

(Reverse Geo-coding)

Address to location database

18 Hormusji Street, Colaba

Vasant Vihar

Image Metadata

latitude: 18° 54′ 59.46″ N,

longitude: 72° 49′ 39.65″ E

Structured Meta Extraction

Nariman House

Income Tax Office

Identify and extract information from tweets

Spatio-Temporal Analysis


Analysis and monetization of social data

  • domain models to enhance thematic

  • relationships


Analysis and monetization of social data

  • who creates?


Analysis and monetization of social data

  • I will, you will, WE will


More at library@kno e sis http knoesis org

More at [email protected]: http://knoesis.org

  • A. Sheth, "A Playground for Mobile Sensors, Human Computing, and Semantic Analytics", IEEE Internet Computing, July/August 2009, pp. 80-85.

  • M. Nagarajan, K. Baid, A. P. Sheth, and S. Wang, "Monetizing User Activity on Social Networks - Challenges and Experiences“, 2009 IEEE/WIC/ACM International Conference on Web Intelligence WI-09, Milan, Italy

  • M. Nagarajan, et al. Spatio-Temporal-Thematic Analysis of Citizen-Sensor Data - Challenges and Experiences, Web Information Systems Engineering- WISE-2009, Poznan, Poland (to appear).

http://knoesis.org/research/semweb/projects/socialmedia/


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