Revision as of 00:05, 15 December 2010

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.

Why Twitris?

Emergence of microblogging platforms such as Twitter, friendfeed etc. have revolutionized how unfiltered, real-time information is disseminated and consumed by citizens. Twitter, has therefore emerged as the preeminent medium for sharing citizen-sensor observations, as was demonstrated in a variety of situations ranging from Mumbai terrorist attack to Iran elections.

While the decentralized information diffusion model offered by twitter has gained momentum and has created avenues for experiential data sharing, millions of observations, shared through tweets, create significant information overload. In many cases it becomes nearly impossible to make sense of the information around a topic of interest. This problem is further compounded by the fact that tweets increasingly integrate other social networking sites (flickr, twitpics) and general Web content(news, Wikipedia, blogs) through embedded links and metadata. Given this data deluge, analyzing the numerous social signals carried by tweets and associated content to find out what is being said about an event (theme), where (spatial), when (temporal), how are key concerns (topics of discussion) changing over a period of time and whether there are regional differences in the opinions on a given topic, can be extremely challenging.

What is Twitris?

In response to this growing data deluge, we have developed Twitris (currently Twitris 2.0) with the vision of performing semantics-empowered analysis of a broad variety of social media content. Specifically, Twitris aims to capture semantics (i.e., meaning and understanding) with spatial, temporal, thematic dimensions, user intentions and sentiments, networking behavior (user interactions patterns and features such as information diffusion and centrality) and other information present in social media. Semantic Web technologies enable its core integration, analysis and data/knowledge sharing abilities. Twitris 2.0, focuses only on content centric analysis , leveraging the relevant Semantic Web technologies, background knowledge, languages, tools where appropriate.

Twitris 2.0 is a Semantic Social Web approach to detect social signals by analyzing massive, event-centric data through:

• Analysis of casual text with spatio-temporal-thematic (STT) bias, to extract event descriptors.
• Capturing semantics from contexts associated with tweets.
• Use of deep semantics (using automatically created domain models) to understand the meaning of standard event descriptors.
• Use of shallow semantics(semantically annotated entities) for knowledge discovery and representation.
• Exposure of processed social data to the public domain, complying with semantic Web standards.
• Semantic Integration of multiple external Web resources (news, articles, images and videos) utilizing the semantic similarity between contexts.

Twitris 2.0 is developed as a multi-layered system where each component acts as part of a pipeline. The system is currently being used for a number of People-Content-Network study experiments and being extended to integrate with SMS and other Web data used by a number of widely deployed open source projects. These include applications used by non governmental organizations (NGO) in developing countries for crisis management (in particular, Ushahidi.org, eMoksha.org and Kiirti.org). Twitris 2.0 is being extended with Twarql technology for limited real-time support and is being adapted for a cloud platform for much higher scalability.

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 Ohio Center of Excellence in Knowledge-Enabled Computing (Kno.e.sis) Center at the Wright State University, Dayton, Ohio (other key themes include semantics-enriched services computing and the sensor Web). 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.

1. A. Jadhav et al., Twitris 2.0 : Semantically Empowered System for Understanding Perceptions From Social Data, ISWC Semantic Web Challenge 2010.
2. A. Sheth, Semantic Integration of Citizen Sensor Data and Multilevel Sensing: A comprehensive path towards event monitoring and situational awareness, February 17, 2009.
3. A. Sheth, Citizen Sensing, Social Signals, and Enriching Human Experience- IEEE Internet Computing, July/August 2009.
4. 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.
5. What are people talking about, Why people write, How people write: Meena Nagarajan's research
6. Real Time Web - A primer Part I and Part II, August 29, 2009

How to Twitris

Internal

For project members only: Twitris Internal Page