The global rise of anti-vaccination movements has led to serious consequences for the public health such as the recent measles outbreak in the United States. The increased promotion of misleading information on vaccinations by social media influencers as well as by media outlets seems to have resulted into a more negative view on vaccinations. The popularity of these social media influencers and the good reputation and authority of the media outlets could have played a substantial role in these developments. The following experimental study will try to explore whether popularity or authority cues can have an impact on the evaluation of the credibility of these two types of sources via an online survey. Furthermore, it aims to examine whether said heuristic cues and resulting conformity effects or the source credibility in general could have an impact on the opinion of recipients on a potential autism-vaccination link. Results have shown that especially authority cues seem to have a positive impact on source credibility evaluations. Furthermore, a high general trust in the media positively influences assessments of source credibility of well-established news outlets. Popularity cues as well as authority cues seem to have a positive effect on the recipients´ opinion. However, authority cues and the resulting effects of informational conformity seem to lead to greater attitude changes. Particularly people with a high need for conformity exhibit considerable attitude changes when exposed to the well-established news outlet as a source. Also, a high perceived source credibility is positively correlated with a desired attitude change. Especially the high perceived credibility of the social media influencer resulted in significant attitude changes. The results underline the importance and positive impact that a perceived authority can have on source credibility assessments and on recipients’ opinions. This highlights the great necessity for self-proclaimed experts on social media platforms and particularly for well-established news outlets to increase their effort to thoroughly and accurately research health-related topics.

Šio darbo objektas yra informacijos, klaidinančios vartotoją, sklaida ir jos įtaka organizacijos įvaizdžiui. Darbo tikslas – remiantis keleto atvejų Lietuvoje analize, atskleisti vartotojus klaidinančios informacijos sklaidos įtaką internetinės prekybos organizacijų įvaizdžiui. Darbo sudaro trys skyriai: pirmoje darbo dalyje pristatoma elektroninio verslo bei internetinės prekybos samprata, pristatomos organizacijos identiteto kūrimo, įvaizdžio formavimo bei palaikymo procesų ir išorinės komunikacijos sąsajos; antroje darbo dalyje analizuojama vartotoją klaidinančios informacijos sklaida bei organizacijos atsakomybės klausimai; trečiojoje darbo dalyje – aprašoma empirinio tyrimo metodologija ir analizuojami tyrimo metu gauti duomenys. Tyrimas buvo atliekamas keliais etapais. Pirmiausia buvo apklausti keturi internetinės prekybos organizacijų Lietuvoje vadovai. Interviu metu išsiaiškinta, kokią įtaką vartotojus klaidinančios informacijos sklaida turi internetinės prekybos organizacijų įvaizdžiui bei komunikacijai. Taip pat buvo atliktas kiekybinis tyrimas, kuris padėjo nubrėžti gaires bei žvalgomąsias tendencijas, ar vartotojams Lietuvoje apskritai yra svarbi adekvačios bei teisingos informacijos apie produktus bei paslaugas sklaida. Tyrimas atskleidė, kad vartotojams yra svarbi teisingos ir adekvačios informacijos apie produktus bei paslaugas sklaida. Jie pripažįsta, jog netoleruoja klaidinančios informacijos, tačiau vis dar susiduria su ja apsipirkdami internetu... [toliau žr. visą tekstą] / The object of investigation of master thesis is spread of misleading information to consumers and its impact to the image of organization. Master thesis aims at revealing the impact of misleading information to consumers on the image of the online sales companies in accordance with few cases of analysis in Lithuania. The thesis consists of three chapters: first chapter deals with online business and sales, also the development of organization identity, forming and sustaining image and the correlation of external communication; spread of misleading information and the responsibility of organization are discussed in the second part; whereas in the third part of the thesis the methodology of empirical research is described, also gathered data is analyzed. Research was performed in few stages. Firstly, four of online sales Lithuanian organizations directors were interviewed. During the interviews it was revealed what kind of impact spread of misleading information to consumers does to the image and communication of organizations. Quantitative research has been performed as well. It helped to determine guidelines and trends related to finding out if consumers in Lithuania need spread of adequate and legitimate information concerned with products and services. Research revealed that consumers need spread of adequate and legitimate information concerned with products and services. Consumers admit that they do not tolerate misleading information, however they still find such... [to full text]

En los últimos años, el consumo de noticias en medios impresos ha sido sustituido en gran medida por el acceso a estas en variados formatos a través de medios digitales y redes sociales. Los bajos costes de acceso a la información y la profusión de las plataformas de comunicación y dispositivos móviles han producido un cambio en los hábitos de consumo de información, la que es recibida desde múltiples fuentes y replicada con inmediatez en un ambiente global. En este contexto, se ha incrementado la desinformación, un problema originado en los albores de la prensa tradicional. En la última década, la desinformación ha alcanzado una escala inmanejable debido al gran volumen de información al que un ciudadano común está expuesto cada día. A esto se suma que la mayoría de estos medios digitales no son arbitrados, y permiten publicar y compartir cualquier tipo de información. En este ambiente es muy probable la proliferación de información engañosa que, en la mayoría de los casos, pretende influir en la opinión pública para perseguir un objetivo económico, social o político subyacente. Esto puede perjudicar a las organizaciones, a las marcas y a las personas, entre otros, derivando en muchas ocasiones en conclusiones precipitadas por parte de los usuarios que la consumen. En este contexto surge el término de la posverdad como una tendencia a priorizar la subjetividad de una interpretación a la verificación de hechos reales. El titular de una noticia está diseñado para resumir sucintamente su contenido, proporcionando al lector una comprensión clara de la misma. Desafortunadamente, en la era de la posverdad, los titulares están más enfocados en atraer la atención del lector que en presentar con precisión el contenido de la noticia. Esto abre una enorme oportunidad para difundir desinformación con la construcción de titulares falsos o distorsionados. Las técnicas tradicionales de verificación de hechos realizadas por humanos son definitivamente impracticables y obsoletas ante la cantidad de textos informativos que se generan incluso cada hora. En este trabajo se abordan soluciones novedosas utilizando Tecnologías de Lenguaje Humano (TLH) y técnicas de Inteligencia Artificial (IA). Esta investigación se ha desarrollado en un área donde se intersecan confusamente diferentes conceptos, herramientas y aproximaciones. Se parte de una ubicación en el estado del arte acerca de las principales soluciones relacionadas con la detección de titulares engañosos, detección de posturas, detección de contradicciones, interrelación entre estos elementos y verificación automática de hechos. A partir del problema enunciado y sus conceptos, se profundiza en diferentes estrategias de solución con la aspiración de proponer una aproximación que permita, con un enfoque suficientemente práctico, aportar a la detección de información engañosa en medios digitales lo que puede convertirse en una herramienta de alerta en el complejo ambiente antes descrito. Entre los elementos considerados, se valora la utilización de ML y de DL como técnicas tradicionales de trabajo en el espacio de estas soluciones, así como sus alcances y limitaciones. Además, se introduce la idea de sustituir el contenido de una noticia por un resumen suficientemente esencial y obtenido de manera automática. La memoria presenta de manera lógica el curso de la investigación que parte de lo conceptual y utiliza el pensamiento deductivo y experimental para alcanzar generalizaciones y aplicarlas deductivamente a la solución de problemas específicos. Con ello, se abordan determinadas tareas que pueden contribuir parcialmente a la solución de parte del problema planteado, se diseñan experimentos y se especifica la solución en el ámbito del idioma español donde no se reportan aportaciones similares. Se propone una arquitectura flexible para la detección de titulares engañosos que ha permitido implementar sobre ella dos prototipos cuyos resultados experimentales y documentados suponen un paso de avance hacia la automatización de esta tarea. Esta arquitectura alcanza resultados notables al ser aplicada sobre dos conjuntos de datos en idioma inglés y español. Siguiendo los principios y las experiencias adquiridas se presenta una aplicación de una arquitectura similar para la detección de noticias falsas, lo que hace presumir su posible generalidad. / Esta tesis ha sido financiada por la Generalitat Valenciana a través del proyecto “SIIA: Tecnologías del lenguaje humano para una sociedad inclusiva, igualitaria, y accesible” (PROMETEU/2018/089); y por FEDER/Ministerio de Ciencia e Innovación - Agencia Estatal de Investigación a través del proyecto “LIVINGLANG: Modelado del comportamiento de entidades digitales mediante tecnologías del lenguaje humano” (RTI2018-094653-B-C21 / C22).

Digitaliseringens ständiga utveckling inom samhället och verksamheter har lett till nya fenomen och förutsättningar vilket har medfört nya utmaningar. Desinformation är ett avdessa begrepp som har fått allt större betydelse inom det digitala samhället som finns idag. Begreppet som har uppmärksammats alltmer syftar till missvisande, felaktig och falskutformad information. Desinformation blir allt vanligare och det problemområde som identifierats är hur verksamheter hanterar existensen av desinformation. Därmed strävade studien mot att svara på frågeställningen: Vilka tillvägagångssätt har verksamheter för att hantera desinformation i sin användning av digital teknik? Studien genomfördes med en kvalitativ forsknings- och metodansats som syftar till att skapa förståelse kring begreppet desinformation, dess bakomliggande faktorer samt vilka tillvägagångssätt verksamheter använder sig av samt hanteringen av begreppet för att minska risken av dess konsekvenser. Datainsamling genomfördes genom en intervjustudie med sju verksamheter samt fem stycken fokusgruppsintervjuer. Resultatet från datainsamlingen påvisade att det finns en bred definition kring betydelsen av desinformation samt att det inom verksamheterna inte finns någon uttalad strategi eller tillvägagångssätt för att hantera desinformation. Det upplevdes finnas tillräckligt med stort förtroende för medarbetarnas egna ansvar i att agera källkritiskt. Befintlig litteratur identifierar att det finns svårigheter kring att upptäcka om informationen är sann eller inte men även att den mänskliga faktorn har betydelse för bedömningen av informationen. Även individens tidigare erfarenheter har betydelse. Det som däremot framkom som studiens slutsats var att följande faktorer var en del av verksamhetens tillvägagångssätt för att avgöra trovärdigheten i information: arbeta med kända aktörer och källor, agera källkritiskt, avgränsa hur intern information hanteras inom verksamheten och bedöma utseende av informationen såsom grammatik och språkbruk. / The digitalization’s constant development in society and in businesses has led to new phenomena and concepts that have not previously existed, which have caused problems. Misinformation is a new concept that has gotten a greater meaning with the digital society that exists today. Misinformation has received increasing attention and refers to misleading, incorrect and falsely designed information. The problem area that is identified is how companies handle the existence of misinformation. The purpose of the study was to answer the research question: What approaches do businesses apply to handle misinformation in their use of digital technology? The study was conducted with a qualitative research and method approach that aims to create an understanding of the concept of misinformation, its underlying factors and what approaches business use when dealing with misinformation to reduce the risk of its consequences. Data collection was conducted through an interview study with seven businesses and five focus group interviews. The results from the data collection showed that there is a broad definition of misinformation and that there is no stated strategy or approach within the operations to deal with misinformation. It was identified that there was enough confidence in the employee's own responsibility in acting source critical. Existing literature identifies that there are difficulties in discovering whether the information is true or not. The human factor has meaning and whether the information is in line with the individual’s opinions. The study's conclusion was that the following factors were a part of the business's approach to determining credibility in information: working with well-known sources, acting with source criticism, defining how information is handled within the business and assessing the appearance of the information such as grammar and language usage.

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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