Job: Research Engineer, NLP on Twitter: Retrieval of Argumentative Structures and Reasoning, Inria Sophia Antipolis, France

Thierry Hamon hamon at LIMSI.FR
Wed Sep 10 20:00:58 UTC 2014

Date: Mon, 8 Sep 2014 10:24:33 +0200 (CEST)
From: Elena Cabrio <elena.cabrio at>
Message-ID: <1747111419.47469556.1410164673640.JavaMail.zimbra at>

Research Engineer - Natural Language Argumentation on Twitter: Retrieval
of Argumentative Structures and Reasoning

We are looking for a Research Engineer with a background in Natural
Language Processing and Knowledge Representation and Reasoning to join
the Inria WIMMICS team ( and the start-up
Vigigloble (
Understanding and interpreting the flow of messages exchanged in real
time on social platforms, like Twitter, raises several important
issues. The big amount of information exchanged on these platforms
represents a significant value for who is able to read and enrich this
multitude of information. Users directly provide this information, and
it is interesting to analyze such data both from the quantitative and
from the qualitative point of view, especially for what concerns
reputation and marketing issues (regarding brands, institutions or
public actors).

Moreover, the automated treatment of this type of data and the
constraints it presents (e.g., limited number of characters, tweets with
a particular writing style, amount of data, real-time communication)
offer a new and rich context for a challenging use of existing tools for
natural language processing. In particular, the goal of the project is
to address the following points:

- Automated selection and annotation of tweets, i.e., retrieval of those
  tweets that can be considered as arguments (like for instance those
  tweets whose content expresses an opinion on a given topic).

- Automated assignment of labels to the type of relation holding between
  arguments (positive relation or negative relation).

- Creation of an argumentation graph illustrating the relations between
  the arguments about a certain subject, and the further application of
  argumentation semantics to compute the set of "winning" arguments
  (i.e., the accepted arguments). This graph-based visualization
  provides a summary of the ongoing discussion on Twitter.

The first step of the project will be the creation and annotation of a
data set extracted from Twitter. This data set will be used as a
benchmark for training and testing NLP algorithms for the automated
detection of the relations between arguments. The second step will
consist in the adaptation of the framework presented in [Cabrio&Villata,
ECAI2012] to the Twitter scenario, with the aim to make it more robust
in terms of processing large volumes of data.
Mandatory requirements for applicants:
1. PhD in Computer Science;
2. Experience in NLP and Knowledge Representation and Reasoning, or in a
   related field (Artificial Intelligence, Machine Learning...);
3. Hands-on experience of at least one programming language (e.g., Java,
   C++) ensure autonomy in completing the technical tasks of the project;
4. Self-motivated, goal-oriented and willing to work in an international
5. Pragmatic and customer oriented;
6. Fluent English is mandatory.
1. Good control of scripting tools (bash, Unix/Linux tools) and of web
2. Experience with automation of NLP processing chains;
3. Fluent in French.
12 months
Gross Salary per month according to the level of diploma and the
experience in the domain: 2500 – 2800€ / month (corresponding to
2100-2300€ net salary / month)

September 15th
Elena Cabrio: elena.cabrio at
Valentino Marra: valentino at
Serena Villata: serena.villata at
[Cabrio&Villata, ECAI2012]
Cabrio E., Villata S. Natural Language Arguments: A Combined
Approach. In Proceedings of the 20th European Conference on Artificial
Intelligence (ECAI 2012), p. 205-210, 2012.
NoDE Benchmark of Natural Language Arguments

More information are available at
and at

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