Abstract:

The main goal of this project is to systematically analyze the expression of irony and sarcasm in social media, in a cross-lingual and multicultural perspective, aiming at its automatic detection.
Automating the detection of irony and sarcasm is yet an unsolved problem. Previous efforts to achieve this aim have been limited in their approach, tending to focus on shallow textual cues indicative of ironic intent. Research has not systematically explored specific linguistic patterns and rhetorical strategies typically used to express verbal and situational irony in text. Moreover, previous studies usually consider these phenomena as a whole, instead of analyzing independently the mechanisms involved in expressing it.

This project aims to answer the following open research questions that are critical to improving irony and sarcasm detection in text mining activities:

i. In social media content, are the linguistic and extra-linguistic mechanisms used to express irony and sarcasm language-dependent?
ii. To what extent does irony expression and representativeness differ across domains, geographical regions, and targets involved?
iii. Which are the most representative linguistic and extra-linguistic devices used to express irony in different types of domains and topics?
iv. How reliable are individuals with respect to identifying and processing ironic messages?
v. Which rhetorical devices are easier to recognize, and which ones are particularly hard to detect, especially by humans not sharing the same cultural and pragmatic context?
vi. Which types of approaches best suit the automatic detection of irony and sarcasm in text? Are we capable of training shallow models to learn these phenomena? Or should we explicitly explore contextual and linguistic information, using advanced NLP strategies?

The main results achieved in the scope of this project will be presented by:

– Paula Carvalho: Identifying Situational Irony in News Headlines
– Sílvio Moreira: Modelling context with user embeddings for sarcasm detection in social media
– Filipe Silva: Computational Detection of Irony in Textual Messages

Date: 2016-Dec-19     Time: 11:00:00     Room: 336

For more information:

• pcc@inesc-id.pt