Twitris
Twitris, a Semantic Web application that facilitates understanding of social perceptions by Semantics-based processing of massive amounts of event-centric data. Twitris 2.0 addresses challenges in large scale processing of social data, preserving spatio-temporal-thematic properties. Twitris 2.0 also covers context based semantic integration of multiple Web resources and expose semantically enriched social data to the public domain. Semantic Web technologies enable the system's integration and analysis abilities.
Developing such a platform is challenging for several reasons.
- One needs to understand the user generated content, often relaxed in terms of grammar and conventional writing practices.
- Twitter in particular imposes a character limit (that makes for creative writing [5]) and has its own conversation lingo (use of # for topic categorization, @ for people references etc.)
- The volume of information is massive (millions of tweets a day), not all of it is relevant to a topic under investigation and not all of it can be stored in the long term.
- Access to potentially available data is also limited due to technical, privacy and business limitations. These have consequences on the statistical processing of content to pull out meaningful social signals.
Twitris as you see is a work in progress, but is rapidly maturing. Technical details can be found in [3]. Data aggregation/cleaning, text processing/analysis etc. are highly compute intensive tasks. Following the "Health Care Reform" that we analyzed on a state wide basis for the US, we will next introduce "Iran Elections" which will provide global country wide assessment of social signals. As of now, our system hosts analysis up until a week prior to the current date and we intend to reduce this period. Analysis of real-time data for more events will be added as time permits.
COMING SOON... Twitris currently performs the Spatial, Temporal and Thematic analysis of the currently popular content on Twitter and so, does answer what is popular. Our current work focuses on analyzing Why and How that content is popular. We address the challenges of finding those elements of content and network properties, which contributes in this information diffusion / virality of the content.
TWITRIS is part of a larger research agenda on semantics-enriched social computing [1, 2, 4] at the Kno.e.sis Center at the Wright State University, Dayton, Ohio (other key themes include semantics-enriched services computing and the sensor Web). For some of the related material, see:
- 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.
- M. Nagarajan et al., Spatio-Temporal-Thematic Analysis of Citizen-Sensor Data - Challenges and Experiences, Tenth International Conference on Web Information Systems Engineering, Oct 5-7, 2009, Poland.
- What are people talking about, Why people write, How people write: Meena Nagarajan's research
- Real Time Web - A primer Part I and Part II, August 29, 2009
How to Twitris
Internal
For project members only: Twitris Internal Page
