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Twarql Tapping Into the Wisdom of the Crowd. Pablo N. Mendes, Pavan Kapanipathi , Alexandre Passant I-SEMANTICS Graz, Austria September 2 nd , 2010. Outline. Introduction Motivation Contributions Use Cases IPad Scenario Location, Sentiment, Recommendations, Competitors System

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Twarql tapping into the wisdom of the crowd

TwarqlTapping Into the Wisdom of the Crowd

Pablo N. Mendes, PavanKapanipathi, Alexandre Passant

I-SEMANTICS

Graz, Austria

September 2nd, 2010


Outline
Outline

  • Introduction

    • Motivation

    • Contributions

  • Use Cases

    • IPad Scenario

    • Location, Sentiment, Recommendations, Competitors

  • System

    • Demo

    • Architecture

    • Activity Flow

    • Annotation Pipeline

  • Conclusion


Tap into the wisdom of the crowd
Tap into the Wisdom of the Crowd?

  • “taking into account the collective opinion of a group of individuals rather than a single expert to answer a question” (Wikipedia)

  • Has been done successfully

    • box-office revenue prediction for movies (CoRR’10)

    • earthquake detection (WWW’10)

  • Can be useful in many scenarios


Social media
Social Media

Information Overload!


Twarql contributions
Twarql Contributions

  • Expressive description of an information need

    • Beyond keywords (uses SPARQL)

  • Flexibility on the point of view

    • Ability to “slice and dice” data in several dimensions: thematic, spatial, temporal, sentiment, etc.

  • Streaming data + background knowledge

    • Enables automatic evolution and serendipity

  • Scalable real time delivery

    • Using sparqlPuSH(SFSW’10)


Use cases ipad scenario
Use Cases (IPad Scenario)

  • Location

    • Retrieve stream of locations where my product is being mentioned right now.

  • Consumer sentiment

    • Retrieve all people that have said negative things about my product.

  • Content suggestion

    • Retrieve all URLs that people recommend with relation to my product.

  • Related entities

    • What competitors are being mentioned with my product?


Use case 1 location query
Use Case 1: Location (query)

  • Retrieve a stream of locations where my product is being mentioned right now.

SELECT ? location

WHERE {

?tweet moat:taggedWithdbpedia:IPad.

?presence opo:currentLocation ?location .

?presence opo:customMessage ?tweet .

}


Use case 1 location
Use Case 1: Location

@anonymized

@anonymized

@anonymized

Loremipsumblabla this is an example tweet

Loremipsumblabla this is an example tweet

Loremipsumblabla this is an example tweet

opo:currentLocation

?presence

?location

SELECT ? location

WHERE {

? tweet moat : taggedWithdbpedia : IPad .

? presence opo: currentLocation ?

location .

? presence opo: customMessage ? tweet .

}

opo:customMessage

moat:taggedWith

dbpedia:IPad

?tweet


Use case 2 consumer sentiment
Use Case 2: Consumer sentiment

Invite users for testing our new launch:

@pablomendes

@terraces

@anonymized

Loremipsumblabla this is an example tweet

@pavankaps

@anotheruser

twarql:sentiment

?user

:Negative

sioc:has_creator

moat:taggedWith

dbpedia:IPad

?tweet


Use case 4 competitors
Use Case 4: Competitors

Background Knowledge (e.g. DBpedia)

IPhone

HPTabletPC

category:Wi-Fi

@anonymized

Loremipsumblabla this is an example tweet

category:Touchscreen

?category

skos:subject

skos:subject

?competitor

skos:subject

moat:taggedWith

dbpedia:IPad

?tweet


Use case 4 competitors contd
Use Case 4: Competitors (contd.)

  • Highlights

    • When a new competitor “appears” in the KB, no change is needed in the query => Automatic Evolution

    • We found interesting products that we didn’t initially consider as competitors of IPad(e.g. IPhone)=> Serendipity


Demonstration
Demonstration

  • Cuebee

    • query formulation

  • Twarql

    • information extraction

    • stream querying

  • sparqlPuSH

    • real time delivery

      Demo link: http://bit.ly/twarql


Architecture
Architecture

Mendes, Passant, Kapanipathi, Sheth. Linked Open Social Signals, Web Intelligence 2010


Conclusion
Conclusion

  • Flexibility and expressiveness in managing real time streams of information!

  • Triples generated for the IPad scenario

    • From June 3rd to June 8th

    • 511,147 tweets

    • 4,479,631 triples

      … and counting!

  • You can generate triples too: http://twarql.sf.net

53,237 positive;

6,739 negative;

451,171 neutral


Thank you
Thank you

  • Connect with us:

    @pablomendes

    @terraces

    @pavankaps

  • Collaborate:

    • http://twarql.sf.net

    • http://wiki.knoesis.org/index.php/Twarql


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