Linked Open Social Signals

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Team: Pablo N. Mendes (Kno.e.sis), Alex Passant (DERI), Pavan Kapanipathi (Kno.e.sis) and Amit P. Sheth (Kno.e.sis).

At any second of the day, millions of Web users are simultaneously publishing opinions, observations and suggestions, or generally "social signals" that may represent invaluable information for businesses and researchers around the world.

In this work we investigate the representation of social signals as structured data in order to enable flexibility in handling the information overload of those interested in collectively analyzing social signals for sensemaking.

This is work in progress by This work extends ideas from Twitris and SMOB.

Twarql Demonstration
Twarql Demonstration http://bit.ly/twarql
SparqlPuSH Demonstration
SparqlPuSH Demonstration http://bit.ly/sparqlpush

Demonstration

We have two demonstration videos and a live demo. The first video demonstrates the user perspective, interacting with the system to formulate a query and obtain microblog posts that match that query. The second video demonstrates the modules of our architecture at work, distributing the microposts via pubsubhubbub.


Architecture

Architecture.png
  • See the workflow between the components of the architecture

Frequently Asked Questions (FAQ)

  • Information relevance: Are tweets interesting at all?
  • Commercial Value: What are the use cases? Is there commercial interest?
    • Social Media Revolution: http://socialnomics.net/
      • Because of the speed in which social media enables communication, word of mouth now becomes world of mouth;
      • BRANDS: 25% of search results for the World’s Top 20 largest brands are links to user-generated content; 34% of bloggers post opinions about products & brands, 78% of consumers trust peer recommendations, Only 14% trust advertisements, Only 18% of traditional TV campaigns generate a positive ROI; We will non longer search for products and services, they will find us via social media.
      • NEWS: 24 of the 25 largest newspapers are experiencing record declines in circulation; 60 millions status updates happen on Facebook daily; We no longer search for the news, the news finds us;
    • Many companies using are using microblogging data. Some companies call it real-time web intelligence or business intelligence

social media,

  • Information Overload: but how can you make sense of so much data?
    • As reported by ReadWriteWeb recently, during an emergency it’s practically impossible to get status updates on things like roads, hospitals, airports, and people using Twitter [1]
    • Twitter as a poor vehicle for marketing [2]. Many people make up hashtags as they tweet, exploding the semantic graph, creating more semantic dispersion. Some promising new tools that can help you quickly put a hashtag in context — or let people easily look up the meaning of the hashtags you launch or use [3]
    • Wouldn’t it be cool if Twitter had a topic backbone and you could snap your tweets to it as you write them? [4]
  • Information Delivery: Push vs Pull
    • Siegel’s rule for information life span: The half-life relevance of a piece of pushed information is about the same as the frequency of the medium. [5]
      • Twitter developed a new set of frameworks @anywhere for adding this Twitter experience anywhere on the web. Imagine being able to follow a New York Times journalist directly from her byline, tweet about a video without leaving YouTube, and discover new Twitter accounts while visiting the Yahoo! home page—and that’s just the beginning. [6]
    • Persistent Search: http://billburnham.blogs.com/burnhamsbeat/2006/04/persistent_sear.html
    • Understanding the Real-Time Web for Web Developers [7]
    • Decentralized Microblogging

Related

  • Bibliography of Research on Twitter & Microblogging [8]
  • Priamos a middleware architecture for real time semantic web [9]

At Kno.e.sis

  • Social Signals @kno.e.sis
  • A. Sheth, Semantic Integration of Citizen Sensor Data and Multilevel Sensing: A comprehensive path towards event monitoring and situational awareness, February 17, 2009.
  • A. Sheth, Citizen Sensing, Social Signals, and Enriching Human Experience- IEEE Internet Computing, July/August 2009.
  • Meenakshi Nagarajan, Karthik Gomadam, Amit P. Sheth, Ajith Ranabahu, Raghava Mutharaju, Ashutosh Jadhav: Spatio-Temporal-Thematic Analysis of Citizen Sensor Data: Challenges and Experiences. WISE 2009: 539-553 [10]

At DERI

At Twitter.com

Semantic Microblogging

  • http://semantictwitter.appspot.com/
    • HyperTwitter is semantic hashtags on Twitter. Associate hashtags together and then performer searches. Clever. Though you might want to create a special Twitter account for doing the associations rather than sending these commands through your main Twitter account.
    • Technical Report

Maybe related

  • Short and Tweet: Experiments on Recommending Content from Information Streams [11]
  • Cheng. Fall'09 class project at iSchool (Berkeley). Classifying Metatweets pdf
  • Klout on health care: [12]
  • Topsy on health care: [13]
  • Krishnamurty, Gill, Arlitt. SIGCOMM'08. A few chirps about twitter. pdf
    • classifies 100,000 users in broadcasters, acquaintances, miscreants or evangelists.

Streaming SPARQL

  • Barbieri et al. C-SPARQL: SPARQL for Continuous Querying WWW'09 poster EDBT'10
  • Barbieri and Della Valle, LDOW2010. A Proposal for Publishing Data Streams as Linked Data (A Position Paper) [14]
  • Streaming SPARQL - Extending SPARQL to Process Data Streams ESWC'08
  • A SPARQL Engine for Streaming RDF Data SITIS'07

Scalability

Publication Timeline

Submitted to WI'2010 on April 2nd, 2010.

Internal

Link to internal project page: http://knoesis.wright.edu/internal/wiki/index.php/Lotter

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