Reaction

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REACTION (Retrieval, Extraction and Aggregation Computing Technology for Integrating and Organizing News) is an initiative for developing a computational journalism platform (mostly) for Portuguese.


Announcements


Previous Announcements

Resources

About

News are no longer simply produced and consumed, but instead continually evolve over time as a cooperative dialog between news outlets and the public at-large. News presentation must fundamentally reflect this, providing anytime organization of the latest events, conveying how story elements developed over time, and integrating the story in the larger world context. In short, the days of simple online aggregation are over; the world has already moved on. While the idea of journalists using computers as information discovery tools goes back several decades, never before has computation been understood to be so tightly integrated with the core of journalistic practice. Journalistic excellence today requires advanced data mining and search technologies, together with novel web services and integrative mashups.

We identify the following important challenges facing the field:

Activities

We research new tools for providing greater automation in news gathering, analysis, and delivery, while respecting practical constraints of news producers and consumers. We emphasize decomposition of stories into finer-grained elements and discovery of implicit relations between them. We also emphasize the relationship between news and social networks, both explicit and implicit, which underlie the news and significantly shape its content, quality, and authority. Hands-on experience in the newsroom will enable practitioners to innovate current practice of news production and identify important avenues for future research in computational journalism.

REACTION is organized in seven complementary research tasks which jointly address the four problem areas identified above:

  1. Mining Resources (lead by: Paula Carvalho, LASIGE)
  2. Entity and Event Tracking (lead by: Francisco Couto, LASIGE)
  3. Web Community Sensing (lead by: Eduarda Mendes Rodrigues, LIACC)
  4. Tracking Information Flow (lead by: Mathew Lease, UTA)
  5. Interaction and Personalization (lead by: Luis Francisco-Revilla, UTA)
  6. Query and Visualization (lead by: Luís Sarmento, SAPO/LIACC
  7. Computational Newsroom (lead by: António Granado, CIMJ)


Funding

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Reaction is a Strategic Research and development project in Interactive and Advanced Digital Media, funded by the CoLab, UT Austin | Portugal International Collaboraboratory for Emerging Technologies

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Research Team

INESC-ID Team:

FEUP/LIACC Team:

UT Austin Team:

UNL/CIMJ Team

Media Industry (PT Comunicações):

Media Industry (Público):

Presentations

Buzz

Publications

M. Bosnjak, E. Oliveira, J. Martins, L. Sarmento and E. Mendes Rodrigues. TwitterEcho - A Distributed Focused Crawler to Support Open Research with Twitter Data. In Proc. of SMANE 2012: Intl. Workshop on Social Media Applications in News and Entertainment, co-located with the ACM 2012 International World Wide Web Conference, WWW 2012, April 2012, Lyon, France.

David S. Batista, João D. Ferreira, Francisco M Couto, and Mário J. Silva. Toponym Disambiguation using Ontology-based Semantic Similarity. In Lecture Notes in Computer Science (LNCS) / Lecture Notes in Artificial Intelligence (LNAI), International Conference on Computational Processing of Portuguese (PROPOR), 17-20 April, 2012, Coimbra, Portugal.

Mário J. Silva, Paula Carvalho, Luís Sarmento. Building a Sentiment Lexicon for Social Judgement Mining. In Lecture Notes in Computer Science (LNCS) / Lecture Notes in Artificial Intelligence (LNAI), International Conference on Computational Processing of Portuguese (PROPOR), 17-20 April, 2012, Coimbra, Portugal.


G. Laboreiro, L. Sarmento and E. Oliveira. Identifying automatic posting systems in microblogs. The 4th Track on Text Mining and Applications (TeMA 2011) in the 15th Portuguese Conference of Artificial Intelligence (EPIA), October 2011, Lisbon, Portugal.

J. Teixeira, L. Sarmento and E. Oliveira. A bootstrapping approach for training a NER with Conditional Random Fields. The 4th Track on Text Mining and Applications (TeMA 2011) in the 15th Portuguese Conference of Artificial ntelligence (EPIA), October 2011, Lisbon, Portugal

Sousa-Silva, R.; Laboreiro, G.; Sarmento, L.; Grant, T.; Oliveira, E. and Maia, B. ‘twazn me!!! ;(’ Automatic Authorship Analysis of Micro-Blogging Messages. Procedings of the 16th International Conference on Applications of Natural Language to Information Systems (NLDB 2011), July 2011, Alicante, Spain.

Paula Carvalho, Luís Sarmento, Mário J. Silva, Jorge Teixeira, Liars and Saviors in a Sentiment Annotated Corpus of Comments to Political Debates.9th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-HTL) Portland, Oregon, USA, June, 2011.
Document

J. Teixeira, L. Sarmento and E. Oliveira. Semi-Automatic Creation of a Reference News Corpus for Fine-Grained Multi-Label Scenarios. Third Workshop on Intelligent Systems and Applications in 6ª Conferência Ibérica de Sistemas e Tecnologias de Informação (CISTI), June 2011, Chaves, Portugal

Mário J. Silva, REACTION TEAM, Notas sobre a Realização e Qualidade do Twitómetro Technical Report. Technical Report . University of Lisbon, Faculty of Sciences,LASIGE, May 2011.
Document

Silvio Moreira, David Batista, Paula Carvalho, Francisco Couto, Mário J. Silva, POWER - Politics Ontology for Web Entity Retrieval. ONTOSE 2011: 5th International Workshop on Ontology, Models, Conceptualization and Epistemology in Social, Artificial and Natural Systems. Lecture Notes in Business Information Processing, 2011, Volume 83, Part 8, 489-500, DOI: 10.1007/978-3-642-22056-2_51.
Document.

Mário J. Silva, Paula Carvalho, Carlos Costa, Luís Sarmento, Automatic Expansion of a Social Judgment Lexicon for Sentiment Analysis Technical Report. TR 10-08. University of Lisbon, Faculty of Sciences, LASIGE, December 2010. doi: 10455/6694

Retrieved from "http://reactionvm03.inesc-id.pt/project/Reaction"
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