About Twitris - Demo Page

TWITRIS is a platform for observing social signals from real time social data as exemplified by Twitter. Real-time social activity has moved to platforms such as Twitter where people share their thoughts, views, opinions and information in microblogging formats. The network structure (e.g., follower subscriptions) and conversational practices (e.g., retweeting) mold an online discourse; the analysis of which can give us near real-time insight into the observations made by people. It also allows us to extract semantic summaries of people observations along spatio-temporal-thematic (STT) dimensions of the data and answer questions of the kinds below:

• What are people talking about today? what are the main topics on their mind? For example, what themes of the "health care debate" are most discussed on date X in state Y in the US?
• For any given theme/topic, how are key concerns (topics of discussion) changing over a period of time?
• Are there regional differences in the opinions on a given theme/topic?

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.

Current Twitris Capabilities:
1. Twitris does clustering of topically relevant crawled Twitter posts based on spatial, temporal and thematic attributes.
2. Twitris extracts potential event descriptors from crawled messages by considering thematic, temporal and spatial importance of phrases.
3. The Twitris user interface facilitates effective browsing of the slices of social perceptions behind an event, highlighting not only what is popular, but also when and where it is popular.
4. Semantic Web technologies play an important role in Twitris. Extracted event descriptors are converted into RDF triples and exposed as a Linked Open Data, containing links to central data sources such as DBpedia.
5. The linkage to DBpedia entities, as well as news articles allows users to seek more information about an event descriptor.

Extention of Twitris with Following New Capabilities:
1. Analyzing Why and How the content is popular on the Twitter by finding those elements of content and network properties, which contributes in this information diffusion / virality of the content.
2. Addition of Twitris timeline will give an option to user to choose a geopoint and explores the timepoints spread on a timeline. The timeline projects URLs and the analysis over time for the selected event OR shows the entities co-occurred with the selected URL over time.
3. Through techniques developed at the Kno.e.sis Center, domain models can be created dynamically using the event context and prominent event descriptors, can be used to facilitate fine grained browsing of concepts.
4. The semantic annotation of Twitter posts can be done to facilitate integration of citizen-sensor observations.
5. Twitris 2.0 with new features is coming shortly.

Twitris Team
Current team members: Ashutosh Jadhav, Pavan Kapanipathi, Pablo Mendes, Meenakshi Nagarajan, Hemant Purohit, Amit Sheth, Wenbo Wang
Past team members: Pramod Ananthram, Karthik Gomadam, Raghava Mutharaju, Vinh Nyugen, Ajith Ranabahu

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:

[1] A. Sheth, Semantic Integration of Citizen Sensor Data and Multilevel Sensing: A comprehensive path towards event monitoring and situational awareness, February 17, 2009.
[2] A. Sheth, Citizen Sensing, Social Signals, and Enriching Human Experience- IEEE Internet Computing, July/August 2009.
[3] 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.
[4] What are people talking about, Why people write, How people write: Meena Najarajan's research
[5] Real Time Web - A primer Part I and Part II, August 29, 2009

How to Twitris