In the sport industry, many stakeholders, including sport organizations, players, coaches, sports reporters, and fans, utilize Twitter. Twitter has become a practical marketing tool, in part, although Twitter users have not been studied in terms of sociodemographics, team identification, media consumption, team related Twitter consumption, or game consumption of their favorite team. Exploring the demographics and consumptive behavior of Twitter users can be valuable for sport organizations to create marketing plans and make managerial decisions. The purpose of this study was to determine the makeup of sport consumers on Twitter for market segmentation purposes and examine their sport media consumption levels, sport-related Twitter usage, team identification level, and team consumption. Differences between Generation X and Y consumers were also determined. An online survey was administered to Twitter users (N = 219). Descriptive statistics, chi-square analyses and MANOVAs revealed characteristics about the users.

With the social media platforms leading the internet in terms of user base and the average time spent, significant amount of data is being generated by these platforms every day. This makes social media platforms a go-to place to understand the reviews, trends, and opinions of the people. Any regular search for a popular topic would result in an abundance of information and thus it is impossible to go through these large amounts of data manually to understand the trends. This thesis discusses techniques for the intra-topic clustering of such social media data and discusses how social media noise increases the redundancy of the search results. Our goal is to filter the amount of redundant information an end-user must review from a regular social media search. The research proposes clustering models based on two string similarity measures Jaccard word token and T-Information distance. Evaluation parameters are introduced and the models are evaluated on clustering a set of current and historical topics to determine which techniques are the most effective. / Graduate

Esta pesquisa tem por objetivo estudar o funcionamento argumentativo do tweet, um gênero textual digital emergente o tweet particularizado pela produção escrita de até cento e quarenta caracteres e que circula somente no ambiente Twitter. O corpus constitui-se de cinquenta tweets do tipo argumentativo produzidos por alunos do 1º ano do Ensino Médio de uma escola privada da cidade de São Paulo, desenvolvidos a partir de uma sequência didática apresentada em aulas de Língua Portuguesa. Em razão de toda produção discursivo-textual não poder ser separada de seu contexto específico de produção, esta pesquisa também examina a rede mundial digital, a Internet, em sua concepção de produtora de ambientes virtuais nos quais circulam variados gêneros textuais digitais emergentes. Tendo em vista que poucos são os estudos sobre o funcionamento da Argumentação em ambientes digitais virtuais, buscamos detectar quais estratégias argumentativas são acionadas para a tomada de um posicionamento em uma condição tão particular de produção, para conhecer o valor argumentativo dos elementos linguísticos e não -linguísticos que utilizados de modo coesivo ou não, constituem o gênero tweet. Por se tratar de uma perspectiva de reflexão linguístico-textual sobre os usos da língua em procedimentos argumentativos, o embasamento teórico deste trabalho fundamenta-se nas referências de Perelman e Olbrechts-Tyteca (2005 [1958]) sobre estratégias argumentativas; na concepção de instâncias argumentativas propostas por Amossy (2007); no conceito e funcionalidade de Redes Sociais e, particularmente do Twitter, apontados por Santaella e Lemos (2010); nos postulados bakhtinianos da constituição e transmutação de gêneros e na perspectiva sociocognitiva-interacionista da Linguística Textual acerca da materialização linguística dos gêneros textuais digitais conforme Marcuschi (2002, 2008, 2010, 2012) Koch (2000, 2002, 2006) e Koch e Elias (2009). Os resultados permitem afirmar que a orientação argumentativa dos aspectos linguísticos presentes nos enunciados e em seus encadeamentos organizam-se no sentido de indicar o posicionamento do locutor que, em função da necessidade de economia de uma economia de escrita, circunscreve seu querer-dizer a determinada dimensão estética / This works objective is to study the argumentative function of the tweet, an emerging genre of digital text that is specified by the written production of a hundred and forty characters and circulates only on the Twitter environment. The corpus is constituted of fifty tweets produced by grade ten students from a private school in São Paulo, developed after a didactic sequence presented in the Portuguese classes. Due to the fact that any discursive-textual production cant be separated from its specific context of production, this research paper also examines the worldwide web, the Internet, as generator of a virtual environment in which a number of emerging digital textual genres circulate. Having in mind that there are few studies about the function of Argumentation in digital virtual environments, we aim at detecting which argumentative strategies are driven to the decision-making in a condition that is so particular of the production, in order to understand the argumentative value of the linguistic and non-linguistic elements that, utilized in a cohesive way or not, constitute the genre tweet. As it is a perspective in the textual- linguistic reflection on the uses of the language in argumentative procedure, this work is based on the references of Perelman and Olbrechts-Tyteca (2005 [1958]) about argumentative strategies; in the conception of argumentative instances proposed by Amossy (2007); in the concept and functionality of Social Networks and, particularly Twitter, pointed out by Santaella and Lemos (2010); Bakhtinian postulates of constitution and transmutation of genres and the sociocognitive-interactionist of Textual Linguistics about the linguistic materialization of digital textual genres on the point of Marcuschi (2002, 2008, 2010, 2012), Koch (1990, 2001, 2002, 2004 2010, 2011), and Koch and Elias (2009). The results grant assertion that the argumentative orientation of the linguistic aspects presented on the statement and in its joints organize themselves on the sense of indicating the speakers positioning that, on the purpose of the necessity of dealing with a restrict number of words, encircles what they mean to a determined aesthetical dimension

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / O presente trabalho discute o processo de reelaboraÃÃo de gÃneros na formaÃÃo das postagens do Twitter. Para tanto, investigamos como o esquema de funcionamento e a dinÃmica de valores dessa rede social inspiram a manipulaÃÃo de diferentes padrÃes genÃricos que, ao serem migrados para o seu interior, sÃo submetidos ao labor de seus usuÃrios. Conduzimos nossa discussÃo à luz da anÃlise de redes sociais praticada por Recuero (2009; 2010), das reflexÃes epistemolÃgicas acerca da natureza dos gÃneros do discurso formuladas por Bakhtin ([1979] 2011), do conceito de propÃsito comunicativo cunhado e esmerado por Swales (1990; 2004), Askhave e Swales (2001) e Bhatia (1993; 2001) e da concepÃÃo de reelaboraÃÃo, conforme vem sendo atualizada desde AraÃjo (2006) atà Zavam (2009) e Costa (2010). Apoiados nessa base teÃrica e metodolÃgica, empreendemos a anÃlise de 195 postagens e 45 questionÃrios respondidos por usuÃrios do Twitter. Em um primeiro momento, a partir dos Ãndices de propagaÃÃo das postagens, observamos como a dinÃmica de funcionamento da rede social influencia a difusÃo e sedimentaÃÃo de arranjos genÃricos formados a partir de padrÃes e gÃneros distintos. Em um segundo momento, voltamo-nos para a forma dos tweets, identificando que estratÃgias foram utilizadas pelos usuÃrios para intervirem nos gÃneros ao elaborarem seus tweets. Por fim, investigamos, nos exemplos do corpus e junto aos usuÃrios questionados, que propÃsitos comunicativos foram atendidos pelas postagens resultantes desse labor. Os resultados mostraram que, no interior do Twitter, hà uma dinÃmica de funcionamento peculiar, que se reflete nas aÃÃes de linguagem dos atores dessa rede social que, motivados pelo desejo de colocarem-se em evidÃncia e ampliarem suas conexÃes, mobilizam e manipulam padrÃes genÃricos distintos por meio de estratÃgias especÃficas. Os arranjos genÃricos gerados a partir desse esquema possuem propÃsitos comunicativos caracterÃsticos, colocados a serviÃo da prÃpria rede social. Acreditamos que a rotina enunciativa caracterÃstica do Twitter, a mobilizaÃÃo de padrÃes genÃricos distintos e a alteraÃÃo de propÃsitos comunicativos sÃo fatores que, somados, dÃo forma a um constante processo de reelaboraÃÃo de gÃneros, cujos produtos sÃo consumidos e propagados dentro da rede social, retroalimentando-a. / This thesis discusses the process of genre re-elaboration in the formation of Twitter posts. We therefore investigated how the functioning scheme and the value dynamics of this social network inspire the manipulation of different genre patterns that, when migrating to the interior, are submitted to its usersâ work. We conduct our discussion in the light of social network analysis practiced by Recuero (2009; 2010), the epistemological reflections on the discourse genre nature formulated by Bakhtin ([1979] 2011), the communicative purpose concept coined and made neat by Swales (1990; 2004), Askhave and Swales (2001) and Bhatia (1993; 2001) and the re-elaboration concept, as been updated since AraÃjo (2006) until Zavam (2009) and Costa (2010). Supported by this theoretical and methodological basis, we undertook an analysis of 195 posts and 45 questionnaires answered by Twitter users. At first, from the post propagation indexes, we observed how the social network functioning dynamics influences the diffusion and the genre arrays sedimentation formed by patterns and distinct genres. In a second step, we turned to the tweet form, detecting that strategies were used by the users in order to intervene in the genres when elaborating their tweets. Finally, we investigated, in the corpus examples and with the users questioned, that communicative purposes were served by the posts resulting from this work. The results showed that, within Twitter, there is a peculiar functioning dynamics, which is reflected in the language actions of the actors of this social network whom, motivated by the desire to put themselves in evidence and broaden their connections, mobilize and manipulate distinct genre patterns by using specific strategies. The genre arrangements generated from this scheme have distinctive communicative purposes, at the service of the social network itself. We believe that the sum of these factors: peculiar enunciative demand, distinct genre pattern mobilization and communicative purpose modification, is set as a genre re-elaboration constant process, whose products are consumed and propagated within the social network, feeding it back.

Mit seiner fokussierten Funktionsweise hat der Mikrobloggingdienst Twitter im Laufe des vergangenen Jahrzehnts eine beachtliche Präsenz als Kommunikationsmedium in diversen Bereichen des Lebens erreicht. Eine besondere Weise, auf die sich die gestiegene Sichtbarkeit Twitters in der täglichen Kommunikation häufig manifestiert, ist die gezielte Verwendung von Hashtags. So nutzen Unternehmen Hashtags um die auf Twitter stattfindenden Diskussionen über ihre Produkte zu bündeln, während Organisatoren von Großveranstaltungen und Fernsehsendungen durch Bekanntgabe ihrer eigenen, offiziellen Hashtags Zuschauer dazu ermutigen, den Dienst parallel zum eigentlichen Event als Diskussionsplattform zu nutzen. [... aus der Einleitung]

Esta pesquisa tem por objetivo estudar o funcionamento argumentativo do tweet, um gênero textual digital emergente o tweet particularizado pela produção escrita de até cento e quarenta caracteres e que circula somente no ambiente Twitter. O corpus constitui-se de cinquenta tweets do tipo argumentativo produzidos por alunos do 1º ano do Ensino Médio de uma escola privada da cidade de São Paulo, desenvolvidos a partir de uma sequência didática apresentada em aulas de Língua Portuguesa. Em razão de toda produção discursivo-textual não poder ser separada de seu contexto específico de produção, esta pesquisa também examina a rede mundial digital, a Internet, em sua concepção de produtora de ambientes virtuais nos quais circulam variados gêneros textuais digitais emergentes. Tendo em vista que poucos são os estudos sobre o funcionamento da Argumentação em ambientes digitais virtuais, buscamos detectar quais estratégias argumentativas são acionadas para a tomada de um posicionamento em uma condição tão particular de produção, para conhecer o valor argumentativo dos elementos linguísticos e não -linguísticos que utilizados de modo coesivo ou não, constituem o gênero tweet. Por se tratar de uma perspectiva de reflexão linguístico-textual sobre os usos da língua em procedimentos argumentativos, o embasamento teórico deste trabalho fundamenta-se nas referências de Perelman e Olbrechts-Tyteca (2005 [1958]) sobre estratégias argumentativas; na concepção de instâncias argumentativas propostas por Amossy (2007); no conceito e funcionalidade de Redes Sociais e, particularmente do Twitter, apontados por Santaella e Lemos (2010); nos postulados bakhtinianos da constituição e transmutação de gêneros e na perspectiva sociocognitiva-interacionista da Linguística Textual acerca da materialização linguística dos gêneros textuais digitais conforme Marcuschi (2002, 2008, 2010, 2012) Koch (2000, 2002, 2006) e Koch e Elias (2009). Os resultados permitem afirmar que a orientação argumentativa dos aspectos linguísticos presentes nos enunciados e em seus encadeamentos organizam-se no sentido de indicar o posicionamento do locutor que, em função da necessidade de economia de uma economia de escrita, circunscreve seu querer-dizer a determinada dimensão estética / This works objective is to study the argumentative function of the tweet, an emerging genre of digital text that is specified by the written production of a hundred and forty characters and circulates only on the Twitter environment. The corpus is constituted of fifty tweets produced by grade ten students from a private school in São Paulo, developed after a didactic sequence presented in the Portuguese classes. Due to the fact that any discursive-textual production cant be separated from its specific context of production, this research paper also examines the worldwide web, the Internet, as generator of a virtual environment in which a number of emerging digital textual genres circulate. Having in mind that there are few studies about the function of Argumentation in digital virtual environments, we aim at detecting which argumentative strategies are driven to the decision-making in a condition that is so particular of the production, in order to understand the argumentative value of the linguistic and non-linguistic elements that, utilized in a cohesive way or not, constitute the genre tweet. As it is a perspective in the textual- linguistic reflection on the uses of the language in argumentative procedure, this work is based on the references of Perelman and Olbrechts-Tyteca (2005 [1958]) about argumentative strategies; in the conception of argumentative instances proposed by Amossy (2007); in the concept and functionality of Social Networks and, particularly Twitter, pointed out by Santaella and Lemos (2010); Bakhtinian postulates of constitution and transmutation of genres and the sociocognitive-interactionist of Textual Linguistics about the linguistic materialization of digital textual genres on the point of Marcuschi (2002, 2008, 2010, 2012), Koch (1990, 2001, 2002, 2004 2010, 2011), and Koch and Elias (2009). The results grant assertion that the argumentative orientation of the linguistic aspects presented on the statement and in its joints organize themselves on the sense of indicating the speakers positioning that, on the purpose of the necessity of dealing with a restrict number of words, encircles what they mean to a determined aesthetical dimension

We want to create a web service that will help users better organize the flood of tweets they receive every day by using machine learning. This was done by experimenting with ways to manually classify training sets of tweets such as using Amazon’s Mechanical Turk and crawling the Internet for large quantities of tweets. Once we acquired good training data, we began building a classifier. We tried NLTK and Stanford NLP as libraries for creating a classifier, and we ultimately created a classifier that is 87.5% accurate. We then built a web service to expose this classifier and to allow any user on the Internet to organize their tweets. We built our web service by using many open source tools, and we discuss how we integrated these tools to create a production quality web service. We run our web service in the Amazon cloud, and we review the costs associated with running in Amazon. Finally we review the lessons we learned and share our thoughts on further work we would like to do in the future. / text

Social media today is an important source of information about various events happening around the world. Among various social networking platforms, microtext based ones such as Twitter are of special interest as they are also a rich source of real-time events. In this thesis, our goal is to study the effectiveness of using Twitter as a social sensor for obtaining real-time information on road traffic conditions. Specifically, we focus on: i) identifying tweets that contain traffic event related information, ii) classify such tweets into six main groups of accident, fire, road construction, police activities, weather and others, iii) extract fine-grained location information about the traffic incident by analyzing tweet text. Our experimental results show that using Twitter as a social sensor for obtaining rich information about traffic events is indeed a promising approach. We show that we can correctly detect traffic related tweets with an accuracy of 81%. Moreover, the accuracy of correctly classifying traffic related tweets into one of the six categories is 97%. Lastly, our experimental results show that using only geo-tags of tweets is not sufficient for fine-grained localization of traffic incidents due to two reasons: i) a vast majority of traffic related tweets do not contain geo-tags, and ii) the location mentioned in the tweet text and the geo-tag of a tweet do not always agree. Such observations prove that fine-grained localization of traffic incidents from tweet must also include analysis of the tweet text using Natural Language Processing techniques.

Mit seiner fokussierten Funktionsweise hat der Mikrobloggingdienst Twitter im Laufe des vergangenen Jahrzehnts eine beachtliche Präsenz als Kommunikationsmedium in diversen Bereichen des Lebens erreicht. Eine besondere Weise, auf die sich die gestiegene Sichtbarkeit Twitters in der täglichen Kommunikation häufig manifestiert, ist die gezielte Verwendung von Hashtags. So nutzen Unternehmen Hashtags um die auf Twitter stattfindenden Diskussionen über ihre Produkte zu bündeln, während Organisatoren von Großveranstaltungen und Fernsehsendungen durch Bekanntgabe ihrer eigenen, offiziellen Hashtags Zuschauer dazu ermutigen, den Dienst parallel zum eigentlichen Event als Diskussionsplattform zu nutzen. [... aus der Einleitung]

Le contenu généré dans les médias sociaux comme Twitter permet aux utilisateurs d'avoir un aperçu rétrospectif d'évènement et de suivre les nouveaux développements dès qu'ils se produisent. Cependant, bien que Twitter soit une source d'information importante, il est caractérisé par le volume et la vélocité des informations publiées qui rendent difficile le suivi de l'évolution des évènements. Pour permettre de mieux tirer profit de ce nouveau vecteur d'information, deux tâches complémentaires de recherche d'information dans les médias sociaux ont été introduites : la génération de résumé rétrospectif qui vise à sélectionner les tweets pertinents et non redondant récapitulant "ce qui s'est passé" et l'envoi des notifications prospectives dès qu'une nouvelle information pertinente est détectée. Notre travail s'inscrit dans ce cadre. L'objectif de cette thèse est de faciliter le suivi d'événement, en fournissant des outils de génération de synthèse adaptés à ce vecteur d'information. Les défis majeurs sous-jacents à notre problématique découlent d'une part du volume, de la vélocité et de la variété des contenus publiés et, d'autre part, de la qualité des tweets qui peut varier d'une manière considérable. La tâche principale dans la notification prospective est l'identification en temps réel des tweets pertinents et non redondants. Le système peut choisir de retourner les nouveaux tweets dès leurs détections où bien de différer leur envoi afin de s'assurer de leur qualité. Dans ce contexte, nos contributions se situent à ces différents niveaux : Premièrement, nous introduisons Word Similarity Extended Boolean Model (WSEBM), un modèle d'estimation de la pertinence qui exploite la similarité entre les termes basée sur le word embedding et qui n'utilise pas les statistiques de flux. L'intuition sous- jacente à notre proposition est que la mesure de similarité à base de word embedding est capable de considérer des mots différents ayant la même sémantique ce qui permet de compenser le non-appariement des termes lors du calcul de la pertinence. Deuxièmement, l'estimation de nouveauté d'un tweet entrant est basée sur la comparaison de ses termes avec les termes des tweets déjà envoyés au lieu d'utiliser la comparaison tweet à tweet. Cette méthode offre un meilleur passage à l'échelle et permet de réduire le temps d'exécution. Troisièmement, pour contourner le problème du seuillage de pertinence, nous utilisons un classificateur binaire qui prédit la pertinence. L'approche proposée est basée sur l'apprentissage supervisé adaptatif dans laquelle les signes sociaux sont combinés avec les autres facteurs de pertinence dépendants de la requête. De plus, le retour des jugements de pertinence est exploité pour re-entrainer le modèle de classification. Enfin, nous montrons que l'approche proposée, qui envoie les notifications en temps réel, permet d'obtenir des performances prometteuses en termes de qualité (pertinence et nouveauté) avec une faible latence alors que les approches de l'état de l'art tendent à favoriser la qualité au détriment de la latence. Cette thèse explore également une nouvelle approche de génération du résumé rétrospectif qui suit un paradigme différent de la majorité des méthodes de l'état de l'art. Nous proposons de modéliser le processus de génération de synthèse sous forme d'un problème d'optimisation linéaire qui prend en compte la diversité temporelle des tweets. Les tweets sont filtrés et regroupés d'une manière incrémentale en deux partitions basées respectivement sur la similarité du contenu et le temps de publication. Nous formulons la génération du résumé comme étant un problème linéaire entier dans lequel les variables inconnues sont binaires, la fonction objective est à maximiser et les contraintes assurent qu'au maximum un tweet par cluster est sélectionné dans la limite de la longueur du résumé fixée préalablement. / User-generated content on social media, such as Twitter, provides in many cases, the latest news before traditional media, which allows having a retrospective summary of events and being updated in a timely fashion whenever a new development occurs. However, social media, while being a valuable source of information, can be also overwhelming given the volume and the velocity of published information. To shield users from being overwhelmed by irrelevant and redundant posts, retrospective summarization and prospective notification (real-time summarization) were introduced as two complementary tasks of information seeking on document streams. The former aims to select a list of relevant and non-redundant tweets that capture "what happened". In the latter, systems monitor the live posts stream and push relevant and novel notifications as soon as possible. Our work falls within these frameworks and focuses on developing a tweet summarization approaches for the two aforementioned scenarios. It aims at providing summaries that capture the key aspects of the event of interest to help users to efficiently acquire information and follow the development of long ongoing events from social media. Nevertheless, tweet summarization task faces many challenges that stem from, on one hand, the high volume, the velocity and the variety of the published information and, on the other hand, the quality of tweets, which can vary significantly. In the prospective notification, the core task is the relevancy and the novelty detection in real-time. For timeliness, a system may choose to push new updates in real-time or may choose to trade timeliness for higher notification quality. Our contributions address these levels: First, we introduce Word Similarity Extended Boolean Model (WSEBM), a relevance model that does not rely on stream statistics and takes advantage of word embedding model. We used word similarity instead of the traditional weighting techniques. By doing this, we overcome the shortness and word mismatch issues in tweets. The intuition behind our proposition is that context-aware similarity measure in word2vec is able to consider different words with the same semantic meaning and hence allows offsetting the word mismatch issue when calculating the similarity between a tweet and a topic. Second, we propose to compute the novelty score of the incoming tweet regarding all words of tweets already pushed to the user instead of using the pairwise comparison. The proposed novelty detection method scales better and reduces the execution time, which fits real-time tweet filtering. Third, we propose an adaptive Learning to Filter approach that leverages social signals as well as query-dependent features. To overcome the issue of relevance threshold setting, we use a binary classifier that predicts the relevance of the incoming tweet. In addition, we show the gain that can be achieved by taking advantage of ongoing relevance feedback. Finally, we adopt a real-time push strategy and we show that the proposed approach achieves a promising performance in terms of quality (relevance and novelty) with low cost of latency whereas the state-of-the-art approaches tend to trade latency for higher quality. This thesis also explores a novel approach to generate a retrospective summary that follows a different paradigm than the majority of state-of-the-art methods. We consider the summary generation as an optimization problem that takes into account the topical and the temporal diversity. Tweets are filtered and are incrementally clustered in two cluster types, namely topical clusters based on content similarity and temporal clusters that depends on publication time. Summary generation is formulated as integer linear problem in which unknowns variables are binaries, the objective function is to be maximized and constraints ensure that at most one post per cluster is selected with respect to the defined summary length limit.