786 resultados para Social media digital


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In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data.

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This research has been conducted within the realm of where today’s digital media society and the timeless concept of cultural identity overlap. The aim of this thesis is to explore the nature of online cultural identity management. By focusing on the social media platform, Pinterest, this study considers the food-pinning behavior of a group of Americans living in Finland and connects their online actions with their cultural identity. Through an examination of Pinterest as a social space, and even a third place, the relative theoretical literature provides and interesting background for a contemporary discussion on the matter. Literature on food as a cultural marker is also brought into consideration. Using the methods of introspection and an adapted version of virtual ethnography, a study was conducted, and ultimately, the analysis of data obtained from the Pinterest boards of ten individuals shows that the vast majority of food-related information in this setting is US-sourced. A questionnaire provides further insight into the individuals’ Pinterest usage. I argue that pinning is an act of online identity management, whether it is a conscious act or a situational effect, and that using Pinterest maintains and even strengthens these individuals’ cultural identity as Americans. This study adds to current discussions pertaining to transnationalism, globalization, and online cultural identity, as well as opens channels for further research on this dynamic topic, which is needed to understand ourselves as cultural beings in the digital age.

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Prior research shows that electronic word of mouth (eWOM) wields considerable influence over consumer behavior. However, as the volume and variety of eWOM grows, firms are faced with challenges in analyzing and responding to this information. In this dissertation, I argue that to meet the new challenges and opportunities posed by the expansion of eWOM and to more accurately measure its impacts on firms and consumers, we need to revisit our methodologies for extracting insights from eWOM. This dissertation consists of three essays that further our understanding of the value of social media analytics, especially with respect to eWOM. In the first essay, I use machine learning techniques to extract semantic structure from online reviews. These semantic dimensions describe the experiences of consumers in the service industry more accurately than traditional numerical variables. To demonstrate the value of these dimensions, I show that they can be used to substantially improve the accuracy of econometric models of firm survival. In the second essay, I explore the effects on eWOM of online deals, such as those offered by Groupon, the value of which to both consumers and merchants is controversial. Through a combination of Bayesian econometric models and controlled lab experiments, I examine the conditions under which online deals affect online reviews and provide strategies to mitigate the potential negative eWOM effects resulting from online deals. In the third essay, I focus on how eWOM can be incorporated into efforts to reduce foodborne illness, a major public health concern. I demonstrate how machine learning techniques can be used to monitor hygiene in restaurants through crowd-sourced online reviews. I am able to identify instances of moral hazard within the hygiene inspection scheme used in New York City by leveraging a dictionary specifically crafted for this purpose. To the extent that online reviews provide some visibility into the hygiene practices of restaurants, I show how losses from information asymmetry may be partially mitigated in this context. Taken together, this dissertation contributes by revisiting and refining the use of eWOM in the service sector through a combination of machine learning and econometric methodologies.

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While a variety of crisis types loom as real risks for organizations and communities, and the media landscape continues to evolve, research is needed to help explain and predict how people respond to various kinds of crisis and disaster information. For example, despite the rising prevalence of digital and mobile media centered on still and moving visuals, and stark increases in Americans’ use of visual-based platforms for seeking and sharing disaster information, relatively little is known about how the presence or absence of disaster visuals online might prompt or deter resilience-related feelings, thoughts, and/or behaviors. Yet, with such insights, governmental and other organizational entities as well as communities themselves may best help individuals and communities prepare for, cope with, and recover from adverse events. Thus, this work uses the theoretical lens of the social-mediated crisis communication model (SMCC) coupled with the limited capacity model of motivated mediated message processing (LC4MP) to explore effects of disaster information source and visuals on viewers’ resilience-related responses to an extreme flooding scenario. Results from two experiments are reported. First a preliminary 2 (disaster information source: organization/US National Weather Service vs. news media/USA Today) x 2 (disaster visuals: no visual podcast vs. moving visual video) factorial between-subjects online experiment with a convenience sample of university students probes effects of crisis source and visuals on a variety of cognitive, affective, and behavioral outcomes. A second between-subjects online experiment manipulating still and moving visual pace in online videos (no visual vs. still, slow-pace visual vs. still, medium-pace visual vs. still, fast-pace visual vs. moving, slow-pace visual vs. moving, medium-pace visual vs. moving, fast-pace visual) with a convenience sample recruited from Amazon’s Mechanical Turk (mTurk) similarly probes a variety of potentially resilience-related cognitive, affective, and behavioral outcomes. The role of biological sex as a quasi-experimental variable is also investigated in both studies. Various implications for community resilience and recommendations for risk and disaster communicators are explored. Implications for theory building and future research are also examined. Resulting modifications of the SMCC model (i.e., removing “message strategy” and adding the new category of “message content elements” under organizational considerations) are proposed.

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This research has been conducted within the realm of where today’s digital media society and the timeless concept of cultural identity overlap. The aim of this thesis is to explore the nature of online cultural identity management. By focusing on the social media platform, Pinterest, this study considers the food-pinning behavior of a group of Americans living in Finland and connects their online actions with their cultural identity. Through an examination of Pinterest as a social space, and even a third place, the relative theoretical literature provides and interesting background for a contemporary discussion on the matter. Literature on food as a cultural marker is also brought into consideration. Using the methods of introspection and an adapted version of virtual ethnography, a study was conducted, and ultimately, the analysis of data obtained from the Pinterest boards of ten individuals shows that the vast majority of food-related information in this setting is US-sourced. A questionnaire provides further insight into the individuals’ Pinterest usage. I argue that pinning is an act of online identity management, whether it is a conscious act or a situational effect, and that using Pinterest maintains and even strengthens these individuals’ cultural identity as Americans. This study adds to current discussions pertaining to transnationalism, globalization, and online cultural identity, as well as opens channels for further research on this dynamic topic, which is needed to understand ourselves as cultural beings in the digital age.

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This flyer promotes a lecture by Cuban blogger and independent journalist Yoani Sanchez, founder of the blog Generacion Y and one of Time Magazine's 100 most influential people in the world. This lecture was held at the Wertheim Performing Arts Center at FIU Modesto A. Maidique Campus on April 1,2013.

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In this paper, we explore the benefits of using social media in an online educational setting, with a particular focus on the use of Facebook and Twitter by participants in a Massive Open Online Course (MOOC) developed to enable educators to learn about the Carpe Diem learning design process. We define social media as digital social tools and environments located outside of the provision of a formal university-provided Learning Management System. We use data collected via interviews and surveys with the MOOC participants as well as social media postings made by the participants throughout the MOOC to offer insights into how participants’ usage and perception of social media in their online learning experiences differed and why. We identified that, although some participants benefitted from social media by crediting it, for example, with networking and knowledge-sharing opportunities, others objected or refused to engage with social media, perceiving it as a waste of their time. We make recommendations for the usage of social media for educational purposes within MOOCs and formal digital learning environments.

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The increasing involvement of individuals in social media over the past decade has enabled firms to pursue new avenues in communication and sponsoring activities. Besides general research on either social media or sponsoring, questions regarding the consequences of a joint activity (sponsoring activities in social media) remain unexplored. Hence, the present study analyses whether the perceived image of the brand and the celebrity endorser credibility of a top sports team influence the perceived brand value of the sponsoring firm in a social media setting. Moreover, these effects are compared between existing customers and non-customers of the sponsoring firm. Interestingly, perceived celebrity endorser credibility plays no role in forming brand value perceptions in the case of the existing customers. Implications for marketing theory and practice are derived.

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Simpósio de Informática (INForum 2015), Covilhã, Portugal. Notes: Best paper award nominee.

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The ever increasing popularity of social media makes it a promising source for the personalization of gameplay experiences. Furthermore, involving social network friends in a game can greatly enrich the satisfaction of the player and also attract potential novel players to a game. This master thesis describes a social overlay designed for desktop games, called GameNshare. It allows players to easily capture and share with multiple social networks game-related screenshots, videos and stories. Additionally, it also provides asynchronous multiplayer game mechanics to directly integrate social network friends in the game. GameNshare was designed to interact with the users in a non-intrusive way allowing them to be in complete control of what is shared. It prevents unsolicited sharing of messages, a key problem in social media integration tools, by the use of built-in message monitoring and anti-spam measures. GameNshare was specially designed for players aged from 18 to 25 years that are regular users of Twitter and Facebook. It was tested by a group of 10 individuals from the target age range that were surveyed to capture their insights on the use of the social overlay. The implemented GameNshare features were well accepted by the testers that were also useful in highlighting features for future development. GameNshare ultimate goal is to make players look and ask for social integration and allow them to take full advantage of their social communities to improve gaming experiences.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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NSBE-UNL

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Generating personalized movie recommendations to users is a problem that most commonly relies on user-movie ratings. These ratings are generally used either to understand the user preferences or to recommend movies that users with similar rating patterns have rated highly. However, movie recommenders are often subject to the Cold-Start problem: new movies have not been rated by anyone, so, they will not be recommended to anyone; likewise, the preferences of new users who have not rated any movie cannot be learned. In parallel, Social-Media platforms, such as Twitter, collect great amounts of user feedback on movies, as these are very popular nowadays. This thesis proposes to explore feedback shared on Twitter to predict the popularity of new movies and show how it can be used to tackle the Cold-Start problem. It also proposes, at a finer grain, to explore the reputation of directors and actors on IMDb to tackle the Cold-Start problem. To assess these aspects, a Reputation-enhanced Recommendation Algorithm is implemented and evaluated on a crawled IMDb dataset with previous user ratings of old movies,together with Twitter data crawled from January 2014 to March 2014, to recommend 60 movies affected by the Cold-Start problem. Twitter revealed to be a strong reputation predictor, and the Reputation-enhanced Recommendation Algorithm improved over several baseline methods. Additionally, the algorithm also proved to be useful when recommending movies in an extreme Cold-Start scenario, where both new movies and users are affected by the Cold-Start problem.

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In this work project we discuss the advantages and disadvantages of social media as a marketing tool. Four international cases were analyzed to provide anecdotal evidence of how social and viral marketing have been used by four firms in very different industries. We reviewed empirical evidence on the topic to discuss the main components of viral marketing. We concluded that positive (electronic) word of mouth, short response time and seeding through high network value customers are the main drivers of the success of a viral marketing campaign. We also conducted a study of the Portuguese telecommunications industry, in particular, the mobile segment. We found that the three main players operating in this market have been using social media successfully as a marketing tool in a strategic approach to the 14-25 years old segment.