[Elsnet-list] CALL FOR PARTICIPATION: EACL Tutorial in Natural Language Processing for Social Media
leon at dcs.shef.ac.uk
Tue Mar 4 19:22:21 CET 2014
CALL FOR PARTICIPATION
EACL Tutorial in Natural Language Processing for Social Media
Gothenburg, Sweden, 26 April 2014
There is an increasing need to interpret and act upon information from
large-volume, social media streams, such as Twitter, Facebook, and forum
posts. However, NLP methods face difficulties when processing social media
text. We call for participation in an intermediate-to-advanced level
tutorial, discussing the state of the art in processing social media text.
Key points of the tutorial include:
- Characterisation of language in social media, and why it is difficult to
- In-depth examination of multiple approaches to core NLP tasks on social
- Discussion of corpus collection and the use of crowdsourcing for
- Practical, legal and ethical aspects of gathering and distributing social
media data and metadata
- Current and future applications of social media information
The tutorial takes a detailed view of key NLP tasks (corpus annotation,
linguistic pre-processing, information extraction and opinion mining) of
social media content. After a short introduction to the challenges of
processing social media, we will cover key NLP algorithms adapted to
processing such content, discuss available evaluation datasets and outline
The core of the tutorial will present NLP techniques tailored to social
media, specifically: language identification, tokenisation, normalisation,
part-of-speech tagging, named entity recognition, entity linking, event
recognition, opinion mining, and text summarisation.
Since the lack of human-annotated NLP corpora of social media content is
another major challenge, this tutorial will cover also crowdsourcing
approaches used to collect training and evaluation data (including paid-for
crowdsourcing with CrowdFlower, also combined with expert-sourcing and
games with a purpose). We will also discuss briefly practical and ethical
considerations, arising from gathering and mining social media content.
The last part of the tutorial will address applications, including
summarisation of social media content, user modelling (geo-location, age,
gender, and personality identification), media monitoring and information
visualisation (for e.g. detecting bushfires, predicting virus outbreaks),
and using social media to predict economical and political outcomes (e.g.
stock price movements, voting intentions).
Web address: http://eacl2014.org/tutorial-social-media
Registration is to be made online via the EACL main registration site:
This tutorial is supported by the CHIST-ERA project uComp (www.ucomp.eu)
and also by the EU FP7 project Pheme (www.pheme.eu).
Hope to see you in Göteborg!
Leon Derczynski and Kalina Bontcheva
Leon R A Derczynski
Research Associate, NLP Group
Department of Computer Science
University of Sheffield, UK
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