Spain

stages 

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for natural language processing and computational linguistics. Often grouped within the field of artificial intelligence, but actually pre-dating the development of artificial intelligence, advances in computational linguistics and natural language processing are now some of the major drivers behind the use of artificial intelligence for commercial and social applications – for example, on-line search, machine translation and with voice-assisted conversational devices.

First established in 1965, the biennial COLING conference is held in diverse parts of the globe and attracts participants from both top-ranked research centers and emerging countries. Today, the most important developments in our field are taking place not only in universities and academic research institutes, but also in industrial research departments and in technological startups. COLING conferences provide opportunities for all these communities to showcase their exciting developments.

COLING 2020

Fake news and deceptive machine-generated text are serious problems threatening modern societies, including in the Arab world. This motivates work on detecting false and manipulated stories online. However, a bottleneck for this research is lack of sufficient data to train detection models. We present a novel method for automatically generating Arabic manipulated (and potentially fake) news stories. Our method is simple and only depends on availability of true stories, which are abundant online, and a part of speech tagger (POS). To facilitate future work, we dispense with both of these requirements altogether by providing AraNews, a novel and large POS-tagged news dataset that can be used off-the-shelf. Using stories generated based on AraNews, we carry out a human annotation study that casts light on the effects of machine manipulation on text veracity. The study also measures human ability to detect Arabic machine manipulated text generated by our method. Finally, we develop the first models for detecting manipulated Arabic news and achieve state-of-the-art results on Arabic fake news detection (macro F1=70.06). Our models and data are publicly available.

Machine Generation and Detection of Arabic Manipulated and Fake News

technical paper

Extractive Summarization System for Annual Reports

Provenance for Linguistic Corpora Through Nanopublications

Reference in Team Communication for Robot-Assisted Disaster Response: An Initial Analysis

A dataset fo anaphora analysis in French Emails

Sequence to Sequence Coreference Resolution

Can Existing Methods Debias Languages Other than English? First Attempt to Analyze and Mitigate Japanese Word Embeddings

E-Commerce Content and Collaborative-based Recommendation using K-Nearest Neighbors and Enriched Weighted Vectors

NLP Technologies and Applications for e-Commerce

The Financial Narrative Summarisation Shared Task (FNS 2020)

Part 6 - Cross-linguistic Studies

poster

https://d3smihljt9218e.cloudfront.net/transcript/4740/subtitle/3d04fe2c0ee49cd0cf6252d0721f1b76.vtt

English (automatic)

Machine Generation and Detection of Arabic Manipulated and Fake News

Downloads

Next from COLING 2020

Extractive Summarization System for Annual Reports

Similar lecture

“What is on your mind?”: Automated Scoring of Mindreading in Childhood and Early Adolescence