Reaching proficiency in Arabic requires a lengthy commitment, and as a result, it is important that students have access to resources that will help them maintain their motivation to learn. Many students are motivated to study because they want to experience the culture of Arabic-speaking countries; however, although the situation is improving, cultural awareness in Arabic language curricula at the elementary level has traditionally been overshadowed. While there are an abundance of online resources available for languages such as Spanish and Japanese that have a consistently strong focus on culture, there are very few comparable online resources for introductory-level Arabic language learners. To address this gap in the resources available to Arabic language learners, I created a website and accompanying social media system called I Heart Arabic. It is directed at introductory students of Arabic and aims to promote cultural awareness, introduce multiple forms of colloquial Arabic, and challenge negative stereotypes of the Arab world. In short, it provides what I have termed "working procrastination" to students of Arabic. "Working procrastination" acts as a break from the rigors of studying Arabic grammar and vocabulary. By focusing on Arab culture in a light-hearted manner, I Heart Arabic can re-motivate students of Arabic language, allowing them to return to their daily studies refreshed and re-energized. / text

In this dissertation, I examine how online conversations as electronic word-of-mouth (eWOM) information via social media networks affect business outcomes. Using data from the movie industry, my goal is to show how conversation quantity and quality, defined here as volumes and valence, on social network sites affect important business outcomes such as sales. Using a dynamic simultaneous equation system, I find that social media conversations can be a precursor to and an outcome of sales. Aggregated data from multiple sources show how social media variables and other key variables—volume, valence, and other information related to movies such as YouTube views, ratings, advertising, production budget, number of screens—contribute to box-office and home video sales through eWOM via social media. Findings highlight that eWOM volume correlates with box-office performance and home video sales: the more positive and strong the conversation, the higher the box office and home video sales. The study extends prior research on WOM and offers insight into how film studios can strategically manage social media to enhance box office and home video revenue. / text

The new social media sites - blogs, micro-blogs, and social networking sites, among others - are gaining considerable momentum to facilitate collaboration and social interactions in general. These sites provide a tremendous asset for understanding social phenomena by providing a wide availability of novel data sources. Recent estimates suggest that social media sites are responsible for as much as one third of new Web content, in the forms of social networks, comments, trackbacks, advertisements, tags, etc. One critical and immediate challenge facing the MIS researchers then becomes - how to effectively utilize this huge wealth of social media data, to facilitate business knowledge discovery and decision making.Among these available data sources, social networks constitute the backbone of almost all social media sites. These network structures provide a rich description of the social scenes and contexts, which is helpful for us to address the above challenge. In this dissertation, I have primarily employed the probabilistic network models, to study various social network related problems arose from the use of social media services. In Chapter 2 and Chapter 3, I studied how information overload can affect the efficiency of information diffusion in online social networks (Delicious.com and Digg.com). Novel diffusion model were proposed to model the observed information overload. The models and their extensions are thoroughly evaluated by solving the Influence Maximization problem related to information diffusion and viral marketing applications. In Chapter 4, I studied the information overload in a micro-blogging application (Twitter.com) using a design science methodology. A content recommendation framework was proposed to help micro-blogging users to efficiently identify quality emergency news feeds. Chapter 5 presents a novel burst detection algorithm concerning identifying and analyzing correlated burst patterns by considering multiple inputs (data streams) that co-evolve over time. The algorithm was later used for discovering burst keywords/tag pairs from online social communities, which are strong indicators of emerging or changing user interests.Chapter 6 concludes this dissertation by highlighting major research contributions and future directions.

Throughout the course of history, presidential campaigning has evolved commensurate with the advancements in technology. FDR mastered the radio, JFK the television and President Barack Obama, the Internet. In both the 2008 and 2012 Presidential campaigns, President Barack Obama used social media via the Internet to understand the voter better than any candidate before his time. Through revolutionary data collection techniques, both offline and online, the Obama campaign obtained vital electorate information. This data was used by the campaign to: target online social media users who were most likely to become politically engaged; and attempt to influence their voting habits, two of the most crucial measures of a successful presidential campaign. This paper analyzes whether the social media campaign strategy deployed by President Barack Obama in both the 2008 and 2012 elections was successful in its attempt to influence the electorate. This is accomplished by evaluating voter turnout and engagement based on targeted demographic groups. Next, I assess how social media has impacted fundraising in the 2st1 century, particularly following the aftermath of the Federal Elections Campaign Act (FECA) in 1974. Finally, I analyze how social media effectively assisted President Obama’s campaign in mobilizing the electorate both online and offline to his benefit.

The non-profit sector is growing, where NPOs compete for scarce resources. Meanwhile, innovation in communication technology requires resources and creativity. Can social media work as an efficient tool for communicating organizational goals and values and how does it enhance trust in NPOs relationship with donors? How do NPOs use ICT and social media in communication to donors and how do they implement functional and emotional communication online?  The research area is approached through a deductive, qualitative, and constructivist perspective. Interviews with two leading NPOs were held, as well as a number of interviews with potential donors. The theoretical framework builds upon Morgan and Hunts and MacMillan et al’s models of trust and commitment. Functional and emotional communication was developed through various theories on online communication. The main findings of this thesis are that Swedish NPOs mainly focus on emotional communication in order to obtain emotional commitment before further developing trust, which is created from functional communication. The investigated NPOs use functional communication to a very little extent.

New event detection, also known as first story detection (FSD), has become very popular in recent years. The task consists of finding previously unseen events from a stream of documents. Despite the apparent simplicity, FSD is very challenging and has applications anywhere where timely access to fresh information is crucial: from journalism to stock market trading, homeland security, or emergency response. With the rise of user generated content and citizen journalism we have entered an era of big and noisy data, yet traditional approaches for solving FSD are not designed to deal with this new type of data. The amount of information that is being generated today exceeds by many orders of magnitude previously available datasets, making traditional approaches obsolete for modern event detection. In this thesis, we propose a modern approach to event detection that scales to unbounded streams of text, without sacrificing accuracy. This is a crucial property that enables us to detect events from large streams like Twitter, which none of the previous approaches were able to do. One of the major problems in detecting new events is vocabulary mismatch, also known as lexical variation. This problem is characterized by different authors using different words to describe the same event, and it is inherent to human language. We show how to mitigate this problem in FSD by using paraphrases. Our approach that uses paraphrases achieves state-of-the-art results on the FSD task, while still maintaining efficiency and being able to process unbounded streams. Another important property of user generated content is the high level of noise, and Twitter is no exception. This is another problem that traditional approaches were not designed to deal with, and here we investigate different methods of reducing the amount of noise. We show that by using information from Wikipedia, it is possible to significantly reduce the amount of spurious events detected in Twitter, while maintaining a very small latency in detection. A question is often raised as to whether Twitter is at all useful, especially if one has access to a high-quality stream such as the newswire, or if it should be considered as sort of a poor man’s newswire. In our comparison of these two streams we find that Twitter contains events not present in the newswire, and that it also breaks some events sooner, showing that it is useful for event detection, even in the presence of newswire.

In this paper, I examine the role of CEO age in predicting the success of startup firms, as measured by social media exposure. I use a novel measure of early-stage growth defined by increased levels of social media and online traction. I hypothesize that the age of the company’s CEO will be negatively correlated with their social media scores while controlling for the company’s total funding amounts and employee counts. My data consists of 250 United States-based startup companies that were founded between 2011 and 2015. Furthermore, they are all relatively successful in that they are still operating and have received between $100 thousand and $10 million of funding. I find that the social media score of a company is negatively impacted by the age of their CEO.

The purpose of this study is to examine the relationship between black millennial political activism and social media use. In Phase One of the study, the attitudes of 126 black 18-29 year olds were measured via survey. Results from the survey show that there is a significant relationship between social media use and political activism. In Phase Two, ten high-scoring participants from Phase One were interviewed and analyzed using thematic coding. Examination of the influence of social media on black millennials can inform strategy used for the advancement of black communities and black activism through widespread, effective communication and an advocacy platform accessible by all.

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Supplier networks today are seeing a complete redirection in their purpose from a decade ago. Supplier networks focused originally on transaction-oriented exchanges for sending purchase orders electronically. However, based on the current increased need to understand business risks, supplier networks are demonstrating a clear shift in emphasis from establishing “transaction-based focus” relationships towards the evolution of network platforms. The Aberdeen Group (2011) demonstrates that 76 per cent of supplier networks increasingly are being used to identify new suppliers and market opportunities. Moreover, with social-networking features similar to Twitter, LinkedIn and Facebook (which are very recent phenomena), supplier networks have become more important in their role of spending management based on the ability to help organisations identify new suppliers while sharing information with other buyer organizations. Therefore, analysing data from supplier networks today has become a necessary strategy for optimizing transaction-focused procurement, in addition to improving supplier relationships. With this in mind, the Social Media Domain Analysis (SoMeDoA) framework has been developed to facilitate the decision-making process for selecting flexible suppliers within the e-procurement-based marketplace and apply it to a real set of data gathered from two social-networking sites (Twitter and LinkedIn). The research contributes a rigorous method that analyses effectively domain concepts and relations between notions from social networks and builds the domain ontology. The effectiveness of the framework, in analysing domain and relations, is evaluated by its application to varying datasets gathered from social networks, including the pharmaceutical domain. This model extrapolates findings from stages in the research and marries elements from various papers and frameworks therein, in order to produce a guideline model for organisations seeking a suitable supplier with whom to work. The results of the evaluation are encouraging, and provide concrete outcomes in an area that is little researched.