Submitted by JOSÉ ESTEVAM DE ALMEIDA PRADO (jeap@jeap.com.br) on 2018-09-17T12:44:09Z No. of bitstreams: 1 Estevam Prado - Dissertação final.pdf: 2266670 bytes, checksum: 312ab5780824b82a4f6e4f41f29aef17 (MD5) / Approved for entry into archive by Joana Martorini (joana.martorini@fgv.br) on 2018-09-17T17:36:31Z (GMT) No. of bitstreams: 1 Estevam Prado - Dissertação final.pdf: 2266670 bytes, checksum: 312ab5780824b82a4f6e4f41f29aef17 (MD5) / Approved for entry into archive by Suzane Guimarães (suzane.guimaraes@fgv.br) on 2018-09-18T13:58:14Z (GMT) No. of bitstreams: 1 Estevam Prado - Dissertação final.pdf: 2266670 bytes, checksum: 312ab5780824b82a4f6e4f41f29aef17 (MD5) / Made available in DSpace on 2018-09-18T13:58:14Z (GMT). No. of bitstreams: 1 Estevam Prado - Dissertação final.pdf: 2266670 bytes, checksum: 312ab5780824b82a4f6e4f41f29aef17 (MD5) Previous issue date: 2018-08-21 / A presente dissertação tem por objetivo estudar a reparação de danos sofridos no mercado de valores mobiliários causados por divulgação de informações falsas ou enganosas. Partindo do papel da informação na formação dos preços de valores mobiliários, e dos danos que pode causar a divulgação de informação falsa ou enganosa, analisamos o tema sob a ótica da responsabilidade civil. O tema tem sido pouco explorado em nosso país até então, e apenas recentemente tem despertado maior atenção em virtude de ações privadas propostas por investidores no exterior em face de importantes companhias aberta brasileiras, com algum desdobramento em nosso país. Para expandir o nosso conhecimento, realizamos pesquisa de direito comparado examinando o tratamento dado nos Estados Unidos e na França aos casos de informação falsa ou enganosa no mercado de valores mobiliários. Verificamos as diferenças existentes e as barreiras à efetiva reparação de danos no mercado de valores mobiliários, concluindo que, embora os tribunais desses países demonstrem disposição de tutelar os interesses lesados, a reparação tem sido ficta. Identificamos como questão problemática a responsabilização da companhia emissora, pois nesse caso não há de fato reparação de danos, mas, sim, a socialização de prejuízos, embora isso possa ser contornado ou mitigado por meio de seguro de responsabilidade e/ou criação de fundo de reparação de danos no mercado de valores mobiliários. / The present dissertation aims to study the repair of damages suffered in the securities market caused by the disclosure of false or misleading information by public companies. Based on the role of information in the formation of securities prices, and the damages that may be caused by the dissemination of false or misleading information, we analyze the issue from a civil liability perspective. The issue has received little attention so far in our country, and only recently has it attracted more attention due to private actions filed by investors abroad in the face of important Brazilian public companies, with some development in our country. To further our knowledge, we conduct comparative law research by examining the treatment given in the United States and France to cases of false or misleading information in the securities market. We have verified the existing differences and barriers to the effective compensation of damages in the securities market, concluding that, although the courts of these countries have shown willingness in protecting the injured interests, reparation has been elusive. We identified the liability of the issuing company as a problematic issue, because in this case there is in fact no compensation of damages, but, rather, the socialization of losses, although this may be overcome or mitigated by means of civil liability insurance and/or creation of a compensation fund for damages in the securities market.

Undoubtedly, the rapid development of information systems and the widespread use of electronic means and social networks have played a significant role in accelerating the pace of events worldwide, such as, in the 2012 Gaza conflict (the 8-day war), in the pro-secessionist rebellion in the 2013-2014 conflict in Eastern Ukraine, in the 2016 US Presidential elections, and in conjunction with the COVID-19 outbreak pandemic since the beginning of 2020. As the number of daily shared data grows quickly on various social networking platforms in different languages, techniques to carry out automatic classification of this huge amount of data timely and correctly are needed. Of the many social networking platforms, Twitter is of the most used ones by netizens. It allows its users to communicate, share their opinions, and express their emotions (sentiments) in the form of short blogs easily at no cost. Moreover, unlike other social networking platforms, Twitter allows research institutions to access its public and historical data, upon request and under control. Therefore, many organizations, at different levels (e.g., governmental, commercial), are seeking to benefit from the analysis and classification of the shared tweets to serve in many application domains, for examples, sentiment analysis to evaluate and determine user’s polarity from the content of their shared text, and misleading information detection to ensure the legitimacy and the credibility of the shared information. To attain this objective, one can apply numerous data representation, preprocessing, natural language processing techniques, and machine/deep learning algorithms. There are several challenges and limitations with existing approaches, including issues with the management of tweets in multiple languages, the determination of what features the feature vector should include, and the assignment of representative and descriptive weights to these features for different mining tasks. Besides, there are limitations in existing performance evaluation metrics to fully assess the developed classification systems. In this dissertation, two novel frameworks are introduced; the first is to efficiently analyze and classify bilingual (Arabic and English) textual content of social networks, while the second is for evaluating the performance of binary classification algorithms. The first framework is designed with: (1) An approach to handle Arabic and English written tweets, and can be extended to cover data written in more languages and from other social networking platforms, (2) An effective data preparation and preprocessing techniques, (3) A novel feature selection technique that allows utilizing different types of features (content-dependent, context-dependent, and domain-dependent), in addition to (4) A novel feature extraction technique to assign weights to the linguistic features based on how representative they are in in the classes they belong to. The proposed framework is employed in performing sentiment analysis and misleading information detection. The performance of this framework is compared to state-of-the-art classification approaches utilizing 11 benchmark datasets comprising both Arabic and English textual content, demonstrating considerable improvement over all other performance evaluation metrics. Then, this framework is utilized in a real-life case study to detect misleading information surrounding the spread of COVID-19. In the second framework, a new multidimensional classification assessment score (MCAS) is introduced. MCAS can determine how good the classification algorithm is when dealing with binary classification problems. It takes into consideration the effect of misclassification errors on the probability of correct detection of instances from both classes. Moreover, it should be valid regardless of the size of the dataset and whether the dataset has a balanced or unbalanced distribution of its instances over the classes. An empirical and practical analysis is conducted on both synthetic and real-life datasets to compare the comportment of the proposed metric against those commonly used. The analysis reveals that the new measure can distinguish the performance of different classification techniques. Furthermore, it allows performing a class-based assessment of classification algorithms, to assess the ability of the classification algorithm when dealing with data from each class separately. This is useful if one of the classifying instances from one class is more important than instances from the other class, such as in COVID-19 testing where the detection of positive patients is much more important than negative ones. / Graduate

This thesis deals with consumer misleading in the field of food labeling. The goal of the thesis was to determine specific products that may mislead consumers by their location and label in particular hypermarkets in Prague and Frýdek-Místek. Analysis of the potential misleading of the consumers has three parts -- examining of an obligatory information on the product package, checking of the location of the products in the shops, and the questionnaire. One part of the thesis deals with law (acts, judgements and other regulations) in the field of food labeling and misleading the consumer.

La présente étude propose d'envisager la publicité dans son ensemble, à l'épreuve de la directive du 11 mai 2005 relative aux pratiques commerciales déloyales. L'étude s'efforcera de mettre en relief les apports de la directive au droit français de la publicité. La directive du 11 mai 2005 entend s'appliquer aux pratiques commerciales déloyales des entreprises vis-à-vis des consommateurs. Pour ce faire elle instaure un cadre juridique inédit. Elle consacre une nouvelle expression : celle de « pratiques commerciales » comprenant la publicité. Cette approche extensive, est accompagnée d'une liste détaillée et conséquente des pratiques déloyales sachant que la directive dont l'objectif est d'assurer un niveau de protection élevé au consommateur tout en contribuant à la réalisation du marché intérieur, s'impose aux États sans que ceux-ci ne puissent prévoir de mesures plus strictes que celles qu'elle prévoit. De ces considérations, émerge l'idée d'absorption de la notion de publicité par celle de pratiques commerciales. Celle-ci s'accompagne de l'absorption du régime juridique de la publicité par celui des pratiques commerciales d'une part, en raison de l'harmonisation prescrite par la directive et d'autre part, en raison de la liste pléthorique de pratiques commerciales déloyales établie par la directive. Ceci permettant de conclure que désormais la publicité n'est qu'un sous-ensemble compris dans l'ensemble plus vaste de celui des pratiques commerciales déloyales. / The present study proposes to consider advertising as a whole, the test of the directive of 11 May 2005 concerning unfair commercial practices. The study will seek tohighlight the contributions of the directive in the french advertising law. The directive of 11May 2005 is intended to protect european consumers against unfair commercial practices.This directive is intended to creates a unique legal framework. It involves a new term: the “commercial practices” including advertising. This broad approach is accompanied by adetailed and consistent list of unfair practices, knowing that the directive which aims to ensure a high level of consumer protection while contributing to the achievement of the internal market, is obligatory for states without that they can not provide more stringentmeasures than those provided. These considerations, the idea emerged to absorb the conceptof advertising that commercial practice. This is accompanied by the absorption of the legal regime of the advertising commercial practices, firstly, due to the harmonization required by the directive and secondly, because of the bloated list of unfair trade practices established by the directive. This allows to conclude that advertising is now a subset included in the larger whole of the unfair trade practices.