Aspectos linguísticos na descrição de notícias satíricas do português do Brasil: uma proposta tipológica
Abstract
The presence of deception on the web and in messaging applications has been a major
contemporary problem. This context generated some initiatives in Linguistics and
Computing to linguistically characterize related texts and automatically detect their
occurrence. According to (RUBIN; CHEN; CONROY, 2015), there are three traditional
types of misleading content: i) fabricated news: produced by what is called the brown
press or tabloids; ii) rumors: news disguised to deceive the public and can be released by
carelessness by traditional news agencies and iii) satirical news: news similar to real news,
however, created for humor purposes. Theoretically, according to Simpson (2003), satire
can be defined, based on a triad, as a discursive practice that establishes and results in an
ironic incongruity between a satirical target, a satirical author and a satirical audience,
and whose purpose is to criticize or mock the satirical target. Thus, if not recognized
as humorous content, satirical news can create difficulties in understanding and false
beliefs in the minds of more inattentive readers. Automatically detecting satirical news,
therefore, proves to be relevant in the linguistic-computational bias, mainly added to the
deficiency of works in the literature that consider the computational analysis of satire
and the inexistence for the Portuguese language. The construction of a corpus of satirical
news and its parallel of true news for Brazilian Portuguese is reported here. The corpus is
composed of a subcorpus of 150 satirical news (22,963 words and 1,212 sentences) extracted
from the Sensationalista website and another subcorpus of 150 real news (107,133 words
and 5,721 sentences) extracted from several online news portals and corresponding to
the articles satirical. The total corpus counts 130 thousand words and 6,900 sentences.
Furthermore, this work proposes to analyze and describe the morphosyntactics aspects,
the difference between the verbal occurrences of satirical news, as well as the main lexical
characteristics found in satirical and true articles. To perform this task, the corpus was
automatically annotated by the PALAVRAS parser (BICK, 2000). The NILC-Metrix
tools (LEAL, 2021) were also used to measure the textual complexity in texts and the
LIWC (PENNEBAKER et al., 2015), which evaluates emotional, cognitive and structural
components of a given text, is based on the use of a dictionary containing sorting words
into categories. Finally, it is expected to contribute to the linguistic description of satirical
news and to create, through the results obtained in this research, bases for future Natural
Language Processing (NLP) works focused on the automatic identification of misleading
content for Brazilian Portuguese.
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