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Media Content Production & Analysis

Home / Research / Work Package 3

About us

Home / Research / Work Package 3

/ Introduction

WP3 will produce novel tools for computational journalism to produce quality generated content in terms of both trustworthiness and engagement as well as fact checking software. Central research questions are: How can we computationally produce unbiased, high-quality multi-modal content effectively? How can we analyse user-generated content accurately to generate more valuable insights? 

Objective: We aim to develop solutions that produce verified and relevant content effectively while employing engaging narratives. We will collaborate closely with media production companies to integrate and test the methods and tools we develop in realistic production settings, thus increasing industry relevance. Our ultimate objective is to analyse user-generated and other media content with respect to quality and validity, extract data, information and knowledge from media content and provide this to algorithms that support (semi-)automated multi-modal content production. 

/ Introduction

WP3 will produce novel tools for computational journalism to produce quality generated content in terms of both trustworthiness and engagement as well as fact checking software. Central research questions are: How can we computationally produce unbiased, high-quality multi-modal content effectively? How can we analyse user-generated content accurately to generate more valuable insights? 

Objective: We aim to develop solutions that produce verified and relevant content effectively while employing engaging narratives. We will collaborate closely with media production companies to integrate and test the methods and tools we develop in realistic production settings, thus increasing industry relevance. Our ultimate objective is to analyse user-generated and other media content with respect to quality and validity, extract data, information and knowledge from media content and provide this to algorithms that support (semi-)automated multi-modal content production. 

/ Introduction

WP3 will produce novel tools for computational journalism to produce quality generated content in terms of both trustworthiness and engagement as well as fact checking software. Central research questions are: How can we computationally produce unbiased, high-quality multi-modal content effectively? How can we analyse user-generated content accurately to generate more valuable insights? 

Objective: We aim to develop solutions that produce verified and relevant content effectively while employing engaging narratives. We will collaborate closely with media production companies to integrate and test the methods and tools we develop in realistic production settings, thus increasing industry relevance. Our ultimate objective is to analyse user-generated and other media content with respect to quality and validity, extract data, information and knowledge from media content and provide this to algorithms that support (semi-)automated multi-modal content production. 

/ People

Bjørnar Tessem

Bjørnar Tessem

Work Package Co-Leader & Task Leader

Andreas Lothe Opdahl

Andreas Lothe Opdahl

Work Package Co-Leader & Task Leader

Duc-Tien Dang-Nguyen

Duc-Tien Dang-Nguyen

Task Leader

Enrico Motta

Enrico Motta

Work Package Advisor & Key Researcher

The Open University

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Vinay Setty

Vinay Setty

Task Leader

Are Tverberg

Are Tverberg

Industry WP3 co-leader

TV 2

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/ Publications

2020

Arne Berven; Ole A. Christensen; Sindre Moldeklev; Andreas Lothe Opdahl; Kjetil A. Villanger

A knowledge-graph platform for newsrooms Journal Article

Computers in Industry, 123 (103321), 2020, (Pre SFI).

Abstract | BibTeX | Links:

Cathal Gurrin; Hideo Joho; Frank Hopfgartner; Liting Zhou; Rami Albatal; Graham Healy; Duc-Tien Dang Nguyen

Experiments in Lifelog Organisation and Retrieval at NTCIR Book Chapter

Evaluating Information Retrieval and Access Tasks, Chapter 13, pp. 187-203, Springer, Singapore, 2020, (Pre SFI).

Abstract | BibTeX | Links:

Danilo Dessì; Francesco Osborne; Diego Reforgiato Recupero; Davide Buscaldi; Enrico Motta; Harald Sack

AI-KG: an automatically generated knowledge graph of artificial intelligence Conference

nternational Semantic Web Conference, Springer, 2020, (Pre SFI).

Abstract | BibTeX | Links:

Vinay Setty; Erlend Rekve

Truth be told: Fake news detection using user reactions on reddit Journal Article

Proceedings of the 29th acm international conference on information knowledge management, pp. 3325–3328, 2020, (Pre SFI).

Abstract | BibTeX | Links:

Enrico Motta; Enrico Daga; Andreas Lothe Opdahl; Bjørnar Tessem

Analysis and design of computational news angles Journal Article

IEEE Access, 8 , pp. 120613-120626, 2020, (Pre SFI).

Abstract | BibTeX | Links:

Andreas Lothe Opdahl; Bjørnar Tessem

Ontologies for finding journalistic angles Journal Article

Software and Systems Modeling, pp. 1-17, 2020, (Pre SFI).

Abstract | BibTeX | Links:

Bjarte Botnevik; Eirik Sakariassen; Vinay Setty

Brenda: Browser extension for fake news detection Journal Article

Proceedings of the 43rd international acm sigir conference on research and development in information retrieval, pp. 2117–2120, 2020, (Pre SFI).

Abstract | BibTeX | Links:

Agnese Chiatti; Enrico Motta; Enrico Daga

Towards a Framework for Visual Intelligence in Service Robotics: Epistemic Requirements and Gap Analysis Journal Article

Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020), pp. 905–916, 2020, (Pre SFI).

Abstract | BibTeX | Links:

Tareq Al-Moslmi; Marc Gallofré Ocaña; Andreas Lothe Opdahl; Csaba Veres

Named entity extraction for knowledge graphs: A literature overview Journal Article

IEEE Access, 8 , pp. 32862-32881, 2020, (Pre SFI).

Abstract | BibTeX | Links:

G. Boato; Duc-Tien Dang Nguyen; F.G.B. De Natale

Morphological filter detector for image forensics applications Journal Article

IEEE Access, 8 , pp. 13549-13560, 2020, (Pre SFI).

Abstract | BibTeX | Links:

2019

Bjørnar Tessem

Analogical News Angles from Text Similarity Conference

Artificial Intelligence XXXVI, (11927), Springer International Publishing, 2019, (Pre SFI).

Abstract | BibTeX | Links:

Enrico Daga; Enrico Motta

Capturing themed evidence, a hybrid approach Conference

roceedings of the 10th International Conference on Knowledge Capture, 2019, (Pre SFI).

Abstract | BibTeX | Links:

Rahul Mishra; Vinay Setty

Hierarchical attention networks to learn latent aspect embeddings for fake news detection Conference

Proceedings of the 2019 acm sigir international conference on theory of information retrieval, Association for Computing Machinery, New York, 2019, (Pre SFI).

Abstract | BibTeX | Links:

Bjørnar Tessem; Andreas Lothe Opdahl

Supporting Journalistic News Angles with Models and Analogies Conference

2019 13th International Conference on Research Challenges in Information Science (RCIS), 2019, (Pre SFI).

Abstract | BibTeX | Links:

2018

Marc Gallofré Ocaña; Lars Nyre; Andreas Lothe Opdahl; Bjørnar Tessem; Christoph Trattner; Csaba Veres

Towards a big data platform for news angles Workshop

Norwegian Big Data Symposium 2018, 2018, (Pre SFI).

Abstract | BibTeX | Links:

Vinay Setty; Katja Hose

Neural embeddings for news events Conference

The 41st international acm sigir conference on research development in information retrieval, Association for Computing Machinery Association for Computing Machinery, New York, 2018, (Pre SFI).

Abstract | BibTeX | Links:

Duc-Tien Dang Nguyen; Michael Alexander Riegler; Liting Zhou; Cathal Gurrin

Challenges and opportunities within personal life archives Conference

Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval, 2018, (Pre SFI).

Abstract | BibTeX | Links:

Angelo Antonio Salatino; Francesco Osborne; Enrico Motta

AUGUR: forecasting the emergence of new research topics Conference

Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries, 2018, (Pre SFI).

Abstract | BibTeX | Links:

2017

Christina Boididou; Stuart Middleton; Zhiwei Jin; Symeon Papadopoulos; Duc-Tien Dang Nguyen; G. Boato; Ioannis (Yiannis) Kompatsiaris

Verifying information with multimedia content on twitter: A comparative study of automated approaches Journal Article

Multimedia Tools and Applications, 77 (12), pp. 15545-15571, 2017, (Pre SFI).

Abstract | BibTeX | Links:

Duc-Tien Dang Nguyen; Luca Piras; Giorgio Giacinto; G. Boato; Francesco G. B. DE Natale

Multimodal Retrieval with Diversification and Relevance Feedback for Tourist Attraction Images Journal Article

14 (4), pp. 1-24, 2017, (Pre SFI).

Abstract | BibTeX | Links:

Vinay Setty; Abhijit Anand; Arunav Mishra; Avishek Anand

Modeling event importance for ranking daily news events Conference

Proceedings of the tenth acm international conference on web search and data mining, Association for Computing Machinery New York, 2017, (Pre SFI).

Abstract | BibTeX | Links:

Lars Nyre; Joao Ribeiro; Bjørnar Tessem

Business models for academic prototypes: A new approach to media innovation Journal Article

he Journal of Media Innovations, 4 (2), pp. 4-19, 2017, (Pre SFI).

Abstract | BibTeX | Links: