Summary
The growing maturity of Natural Language Processing (NLP) techniques and resources is drastically changing the landscape of many application domains which are dependent on the analysis of unstructured data at scale. The financial domain, with its dependency on the interpretation of multiple unstructured and structured data sources and with its demand for fast and comprehensive decision making is already emerging as a primary ground for the experimentation of NLP, Web Mining and Information Retrieval (IR) techniques. This challenge focuses on advancing the state-of-the-art of aspect-based sentiment analysis and opinion-based Question Answering for the financial domain.

This challenge aims to provide an experimentation and discussion ground for novel NLP approaches targeting the interpretation of financial data using the tasks of aspect-based sentiment analysis and opinionated Question Answering(QA) as motivational scenarios. The challenge aims at catalyzing theoretical and empirical discussions around principles, methods and resources focused on financial data. A special emphasis is given to multi-lingual and multiple data sources.

While previous tasks and challenges have focused on, multilingual document, message sentence or even entity level sentiment classification, no challenge that we are aware of attempts to analyse to the aspect level. Moreover such tasks often do not focus beyond the English language for such fine grained sentiment analysis. In addition, research in Question Answering(QA) from opinionated datasets is also under-explored.
Topics of particular interest to be discussed and developed within the task include (but are not limited to):
-Aspect-oriented sentiment analysis and opinion mining.
-Aspect-identification extraction/classification for finance for opinion mining.
-Question Answering and opinion-based Question Answering over financial text.
-Multi-lingual sentiment analysis.
-Linguistic analysis tools for the financial domain, in particular financial social media (e.g. tokenisation, part-of-speech tagging, normalization, parsing)
-Sentiment classification on financial texts;
-Analysing and understanding linguistic phenomena associated with financial text corpora (including the sub-language of financial microblogs);
-New semantic and ontological models for finance;
-Construction and application of distributional semantic models on finance;
-Lexical resources for the financial domain;

Timeline:

* Publication of the training data: December 5st , 2018.
* Challenge papers submission deadline: February 4th, 2018.
* Challenge papers acceptance notification: February 14th, 2018.
* Challenge test data published and submission of results: February 14th, 2018.

Submission:

The Web Conference Challenges is an official track of the conference. We request from participants to provide, in addition to their participation to the challenge, a paper describing the proposed solution and, when relevant, self-assessments related to the defined criteria for evaluation. These papers will be published in the official satellite proceedings of the conference.

Organizers:

Macedo Maia, Department of Computer Science and Mathematics, University of Passau.
André Freitas, School of Computer Science, University of Manchester.
Alexandra Balahur, Text and Data Mining Unit, European Commission's Joint Research Centre.
Manel Zarrouk, Insight Centre for Data Analytics, National University of Ireland, Galway.
Brian Davis, Department of Computer Science, Maynooth University.