scholarly journals Deteção de linguagem tendenciosa em decisões judiciais

2021 ◽  
pp. 203-217
Author(s):  
Alexandra Guedes Pinto ◽  
Catarina Vaz Warrot ◽  
Henrique Lopes Cardoso ◽  
Isabel Margarida Duarte ◽  
Rui Sousa-Silva
Keyword(s):  
Computational Linguistics ◽  
Language Processing ◽  
Gender Violence ◽  
Public Access ◽  
Court Decisions ◽  
Linguistic Expression ◽  
Linguistic Features ◽  
Future Possibility ◽  
Text Genre ◽  
Discourse Organization

The linguistic expression of subjectivity is a complex phenomenon that has been the object of reflection by several sub-areas of Linguistics and, more recently, of Computational Linguistics. Linguistic subjectivity, in terms of the linguistic expression of the speaker's opinions and attitudes, affects all levels of discourse organization and is present, to different degrees, in diverse textual genres. Subjectivity and bias are connected, in the sense that the presence of bias in discourse has been related, both in Linguistics and Computational Linguistics, to the occurrence of signs of subjectivity. Court decisions are an argumentative text genre that may convey traces of subjectivity but should not be biased. As a discourse that represents the State’s position on social matters, it should reflect the principle of Equality. Nonetheless, a preliminary analysis of cases of gender violence reveals that this is not always the case. The research proposed in this paper aims to study the linguistic formulations that convey subjectivity and bias in court decisions on gender violence against women. The goal is to develop a linguistic model to detect these instances of bias, with a future possibility of application in a tool for automatic detection of gender bias in discourse, fueled by Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques. A corpus of court decisions on gender violence has been extracted from the public access database of Instituto de Gestão Financeira e Equipamentos da Justiça (IGFEJ), and has been subject to analysis. A set of examples has been compiled in the analytical section of this study, demonstrating the possibility of connecting certain linguistic features, such as mitigation and intensification mechanisms, evidential expressions and counter-argumentative movements, to the presence of subjectivity and bias in discourse.

scholarly journals Linguistic feature of anorexia nervosa: a prospective case–control pilot study

2021 ◽  
Author(s):  
Vittoria Cuteri ◽  
Giulia Minori ◽  
Gloria Gagliardi ◽  
Fabio Tamburini ◽  
Elisabetta Malaspina ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Language Processing ◽  
Statistical Significance ◽  
Case Control ◽  
Pathological Process ◽  
Linguistic Features ◽  
Level Of Evidence ◽  
Linguistic Feature ◽  
Linguistic Markers ◽  
Clinical Conditions

Abstract Purpose Attention has recently been paid to Clinical Linguistics for the detection and support of clinical conditions. Many works have been published on the “linguistic profile” of various clinical populations, but very few papers have been devoted to linguistic changes in patients with eating disorders. Patients with Anorexia Nervosa (AN) share similar psychological features such as disturbances in self-perceived body image, inflexible and obsessive thinking and anxious or depressive traits. We hypothesize that these characteristics can result in altered linguistic patterns and be detected using the Natural Language Processing tools. Methods We enrolled 51 young participants from December 2019 to February 2020 (age range: 14–18): 17 girls with a clinical diagnosis of AN, and 34 normal-weighted peers, matched by gender, age and educational level. Participants in each group were asked to produce three written texts (around 10–15 lines long). A rich set of linguistic features was extracted from the text samples and the statistical significance in pinpointing the pathological process was measured. Results Comparison between the two groups showed several linguistics indexes as statistically significant, with syntactic reduction as the most relevant trait of AN productions. In particular, the following features emerge as statistically significant in distinguishing AN girls and their normal-weighted peers: the length of the sentences, the complexity of the noun phrase, and the global syntactic complexity. This peculiar pattern of linguistic erosion may be due to the severe metabolic impairment also affecting the central nervous system in AN. Conclusion These preliminary data showed the existence of linguistic parameters as probable linguistic markers of AN. However, the analysis of a bigger cohort, still ongoing, is needed to consolidate this assumption. Level of evidence III Evidence obtained from case–control analytic studies.

The Verbmobil prototype system – a software engineering perspective

1999 ◽  
Vol 5 (1) ◽  
pp. 95-112 ◽  
Author(s):  
THOMAS BUB ◽  
JOHANNES SCHWINN
Keyword(s):  
Software Engineering ◽  
Computational Linguistics ◽  
Language Processing ◽  
System Integration ◽  
Evolutionary Process ◽  
Prototype System ◽  
Functional Architecture ◽  
Seamless Integration ◽  
Extensible Software ◽  
Transfer Problems

Verbmobil represents a new generation of speech-to-speech translation systems in which spontaneously spoken language, speaker independence and adaptability as well as the combination of deep and shallow approaches to the analysis and transfer problems are the main features. The project brought together researchers from the fields of signal processing, computational linguistics and artificial intelligence. Verbmobil goes beyond the state-of-the-art in each of these areas, but its main achievement is the seamless integration of them. The first project phase (1993–1996) has been followed up by the second project phase (1997–2000), which aims at applying the results to further languages and at integrating innovative telecooperation techniques. Quite apart from the speech and language processing issues, the size and complexity of the project represent an extreme challenge on the areas of project management and software engineering:[bull ] 50 researchers from 29 organizations at different sites in different countries are involved in the software development process,[bull ] to reuse existing software, hardware, knowledge and experience, only a few technical restrictions could be given to the partners.In this article we describe the Verbmobil prototype system from a software-engineering perspective. We discuss:[bull ] the modularized functional architecture,[bull ] the flexible and extensible software architecture which reflects that functional architecture,[bull ] the evolutionary process of system integration,[bull ] the communication-based organizational structure of the project,[bull ] the evaluation of the system operational by the end of the first project phase.

Finite-State Technology

2018 ◽  
Author(s):  
Mans Hulden
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Computational Linguistics ◽  
Language Processing ◽  
Finite State Machines ◽  
Regular Languages ◽  
Finite State Automata ◽  
State Machines ◽  
Computational Phonology ◽  
Finite State

Finite-state machines—automata and transducers—are ubiquitous in natural-language processing and computational linguistics. This chapter introduces the fundamentals of finite-state automata and transducers, both probabilistic and non-probabilistic, illustrating the technology with example applications and common usage. It also covers the construction of transducers, which correspond to regular relations, and automata, which correspond to regular languages. The technologies introduced are widely employed in natural language processing, computational phonology and morphology in particular, and this is illustrated through common practical use cases.

scholarly journals The Sentiments Analysis of Donald Trump and Jokowi’s Twitters on Covid-19 Policy Dissemination

Webology ◽  
2021 ◽  
Vol 18 (1) ◽  
pp. 389-405
Author(s):  
Rahmad Agus Dwianto ◽  
Achmad Nurmandi ◽  
Salahudin Salahudin
Keyword(s):  
Data Collection ◽  
Sentiment Analysis ◽  
Computational Linguistics ◽  
Language Processing ◽  
The Us ◽  
Twitter Account ◽  
Policy Dissemination ◽  
Collection Period ◽  
Source Materials

As Covid-19 spreads to other nations and governments attempt to minimize its effect by introducing countermeasures, individuals have often used social media outlets to share their opinions on the measures themselves, the leaders implementing them, and the ways in which their lives are shifting. Sentiment analysis refers to the application in source materials of natural language processing, computational linguistics, and text analytics to identify and classify subjective opinions. The reason why this research uses a sentiment case study towards Trump and Jokowi's policies is because Jokowi and Trump have similarities in handling Covid-19. Indonesia and the US are still low in the discipline in implementing health protocols. The data collection period was chosen on September 21 - October 21 2020 because during that period, the top 5 trending on Twitter included # covid19, #jokowi, #miglobal, #trump, and #donaldtrump. So, this period is most appropriate for taking data and discussing the handling of Covid-19 by Jokowi and Trump. The result shows both Jokowi and Trump have higher negative sentiments than positive sentiments during the period. Trump had issued a controversial statement regarding the handling of Covid-19. This research is limited to the sentiment generated by the policies conveyed by the US and Indonesian Governments via @jokowi and @realDonaldTrump Twitter Account. The dataset presented in this research is being collected and analyzed using the Brand24, a software-automated sentiment analysis. Further research can increase the scope of the data and increase the timeframe for data collection and develop tools for analyzing sentiment.

scholarly journals Mere fugl end fisk. Sproglige ligheder og forskelle bag typologisering af tekster

2017 ◽  
Vol 11 (20) ◽  
pp. 79
Author(s):  
Lita Lundquist
Keyword(s):  
Computer Program ◽  
Linguistic Expression ◽  
Cognitive Content ◽  
Linguistic Features ◽  
Contrast Model ◽  
Text Types

The work reported here explores a cognitive-communicative hypothesis of text ty-pology that text types defined on external communicative criteria also exhibit typical constellations of linguistic features text-internally. Inspired by Tversky's (1981) math-ematical "contrast model of similarities", a French contract, a law and a judgment were analyzed using the computer program 'Cohérelle' into sets of syntactic, semantic, pragmatic, and textlinguistic features. Subsequent computations showed that reliable similarities (in the linguistic expression of cognitive content) and differences (in the use of communicative grounding expressions) could in fact be distinguished among the linguistic features of the three text exemplars, thus permitting the postulation of dif-ferent types on text-internal linguistic grounds.

scholarly journals Developing and Analyzing a Spanish Corpus for Forensic Purposes

2019 ◽  
Vol 3 ◽  
Author(s):  
Ángela Almela ◽  
Gema Alcaraz-Mármol ◽  
Arancha García-Pinar ◽  
Clara Pallejá
Keyword(s):  
Data Collection ◽  
Language Processing ◽  
Ad Hoc ◽  
Semantic Analysis ◽  
Linguistic Features ◽  
Natural Language Processing Tool ◽  
Check Method ◽  
Spanish Universities ◽  
Gender Based ◽  
Main Instrument

In this paper, the methods for developing a database of Spanish writing that can be used for forensic linguistic research are presented, including our data collection procedures. Specifically, the main instrument used for data collection has been translated into Spanish and adapted from Chaski (2001). It consists of ten tasks, by means of which the subjects are asked to write formal and informal texts about different topics. To date, 93 undergraduates from Spanish universities have already participated in the study and prisoners convicted of gender-based abuse have participated. A twofold analysis has been performed, since the data collected have been approached from a semantic and a morphosyntactic perspective. Regarding the semantic analysis, psycholinguistic categories have been used, many of them taken from the LIWC dictionary (Pennebaker et al., 2001). In order to obtain a more comprehensive depiction of the linguistic data, some other ad-hoc categories have been created, based on the corpus itself, using a double-check method for their validation so as to ensure inter-rater reliability. Furthermore, as regards morphosyntactic analysis, the natural language processing tool ALIAS TATTLER is being developed for Spanish.  Results shows that is it possible to differentiate non-abusers from abusers with strong accuracy based on linguistic features.

Aspect-Based Sentiment Analysis of Online Product Reviews

2017 ◽  
pp. 175-191 ◽  
Author(s):  
Vinod Kumar Mishra ◽  
Himanshu Tiruwa
Keyword(s):  
Sentiment Analysis ◽  
Computational Linguistics ◽  
Language Processing ◽  
Future Trend ◽  
Product Reviews ◽  
Customer Reviews ◽  
Part Of Speech ◽  
Lexical Approach ◽  
Sentiment Score ◽  
Pos Tagger

Sentiment analysis is a part of computational linguistics concerned with extracting sentiment and emotion from text. It is also considered as a task of natural language processing and data mining. Sentiment analysis mainly concentrate on identifying whether a given text is subjective or objective and if it is subjective, then whether it is negative, positive or neutral. This chapter provide an overview of aspect based sentiment analysis with current and future trend of research on aspect based sentiment analysis. This chapter also provide a aspect based sentiment analysis of online customer reviews of Nokia 6600. To perform aspect based classification we are using lexical approach on eclipse platform which classify the review as a positive, negative or neutral on the basis of features of product. The Sentiwordnet is used as a lexical resource to calculate the overall sentiment score of each sentence, pos tagger is used for part of speech tagging, frequency based method is used for extraction of the aspects/features and used negation handling for improving the accuracy of the system.

Advances in Computational Linguistics and Text Processing Frameworks

2020 ◽  
pp. 217-244
Author(s):  
Ayush Srivastav ◽  
Hera Khan ◽  
Amit Kumar Mishra
Keyword(s):  
Neural Networks ◽  
Natural Language Processing ◽  
Natural Language ◽  
Computational Linguistics ◽  
Language Processing ◽  
Text Processing ◽  
Named Entity Recognition ◽  
Entity Recognition ◽  
Named Entity ◽  
Part Of Speech

The chapter provides an eloquent account of the major methodologies and advances in the field of Natural Language Processing. The most popular models that have been used over time for the task of Natural Language Processing have been discussed along with their applications in their specific tasks. The chapter begins with the fundamental concepts of regex and tokenization. It provides an insight to text preprocessing and its methodologies such as Stemming and Lemmatization, Stop Word Removal, followed by Part-of-Speech tagging and Named Entity Recognition. Further, this chapter elaborates the concept of Word Embedding, its various types, and some common frameworks such as word2vec, GloVe, and fastText. A brief description of classification algorithms used in Natural Language Processing is provided next, followed by Neural Networks and its advanced forms such as Recursive Neural Networks and Seq2seq models that are used in Computational Linguistics. A brief description of chatbots and Memory Networks concludes the chapter.

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