ࡱ> .0-bjbjUU >??  0) 5T============^ ==y0====<========================= :Resumo Com o surgimento de aplicativos baseados emcrowdsourcing que fazem uso intenso de informaes fornecidas espontaneamente por uma multido de usurios geralmente desconhecidos , a participao dos usurios na produo de contedo digital vem crescendo continuamente, ampliando o papel que estes exerciam em pocas anteriores Web 2.0. Neste cenrio, os usurios alm de consumir os contedos oferecidos, tm tambm a responsabilidade de produzi-los. Entretanto, o volume de informaes gerado nestes aplicativos muito grande e fazer uma anlise de todo o contedo disponibilizado invivel do ponto de vista prtico. Ainda assim, so necessrios critrios para decidir se um contedo pode ser confivel ou no. Um elemento que norteia bem as nossas decises no mundo real a reputao do responsvel pela publicao de uma informao. A reputao diz respeito fama de um produtor digital, e est relacionada confiana nas informaes fornecidas por este usurio. Esses aplicativos devem fazer uso de sistemas de reputao para auxiliar na identificao da reputao dos usurios produtores de contedo. Esses sistemas ajudam os usurios a participar de forma mais consciente, ajudando-os em tomadas de decises. Assim, surge a questo: quais so as estratgias adotadas para comunicar a reputao desses usurios? Como essas estratgias so percebidas pelos usurios? Sendo assim, como essas estratgias afetam a interao humano-computador? Esse trabalho apresenta os estudos realizados em dois aplicativos baseados emcrowdsourcing, visando explorar e identificar as estratgias para comunicar a reputao de usurios produtores de contedo e, alm disso, avaliar a sua comunicabilidade. Nossa metodologia se fundamentou na Engenharia Semitica e adotou mtodos de avaliao de IHC com foco na comunicabilidade e testes de observaes com usurios. Os resultados obtidos permitiram categorizar as estratgias encontradas, identificar as potenciais influncias na interao humano-computador neste contexto de uso, e oferecer uma detalhada anlise comparativa sobre essas questes. Com isso, espera-se auxiliar os desenvolvedores e a comunidade de pesquisa em IHC nas questes de design e avaliao de aplicativos baseados emcrowdsourcing. Palavras-chave: Crowdsourcing; Engenharia Semitica; Interao Humano-Computador; Reputao. ABSTRACT Since the arising of crowdsourcing-based applications that make intensive use of information provided voluntarily by a crowd of generally unknown users, the participation of users in digital content production has been growing continuously, expanding the role they played in former times Web 2.0. In this scenario, users beyond to consume the content offered, also have a responsibility to produce them. However, due to the huge volume of information generated, analyzing all the available content is not feasible from a practical point of view. Nevertheless, criteria are needed to decide whether some content can be trusted or not. One element that guides our decisions in the real world is the reputation of the person responsible for the publication of information. The reputation means the "fame" of a digital producer, and is related to reliance on the information provided by this user. These applications should make use of reputation systems to help to identify the reputation of the users that are producers of content. These systems help users to participate more consciously, helping them in making decisions. This way, a question arises: what are the strategies adopted to communicate the reputation of these users? How these strategies are perceived by users? This way, how these strategies affect the human-computer interaction? This research presents the studies in two applications based on crowdsourcing, aiming to explore and identify strategies for communicating the reputation of producers and users of content, in addition, to evaluate their communicability. Our methodology was based on Semiotics Engineering and adopted HCI evaluation methods focused on communicability and observations of user testing. From these we were able to categorize the strategies found, identify potential influences on humancomputer interaction in this context of use, and provide a detailed comparative analysis of these issues. We expect these outcomes will be useful to developers and to the HCI research community on design issues and evaluation of crowdsourcing-based applications. 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