Intweetive Text Summarization

The amount of user generated contents from various social medias allows analyst to handle a wide view of conversations on several topics related to their business. Nevertheless keeping up-to-date with this amount of information is not humanly feasible. Automatic Summarization then provides an intere...

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Published in:arXiv.org 2020-01
Main Authors: Cossu, Jean Valère, Torres-Moreno, Juan-Manuel, SanJuan, Eric, El-Bèze, Marc
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Social networks
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creator Cossu, Jean Valère
Torres-Moreno, Juan-Manuel
SanJuan, Eric
El-Bèze, Marc
description The amount of user generated contents from various social medias allows analyst to handle a wide view of conversations on several topics related to their business. Nevertheless keeping up-to-date with this amount of information is not humanly feasible. Automatic Summarization then provides an interesting mean to digest the dynamics and the mass volume of contents. In this paper, we address the issue of tweets summarization which remains scarcely explored. We propose to automatically generated summaries of Micro-Blogs conversations dealing with public figures E-Reputation. These summaries are generated using key-word queries or sample tweet and offer a focused view of the whole Micro-Blog network. Since state-of-the-art is lacking on this point we conduct and evaluate our experiments over the multilingual CLEF RepLab Topic-Detection dataset according to an experimental evaluation process.
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subjects Social networks
Summaries
title Intweetive Text Summarization
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