Whereas the traditional rhetorical practices of memory and delivery were directly connected to the body of the speaker, I argue that when communication is embodied on digital networks, the processes underlying memory and delivery—the coordination of individual and text and the use of embodied affordances to present a text, respectively— are expressed in different ways. Resonance, or the act of bringing two structures into coordination with each other, and switching, or the act of making connections between two networks, fulfill the role of memory in digital networks, coordinating the actions of different networks. Similarly, the protocol, or the technical and cultural rules of networks, and the program, or the emergent behavior, of a network must be taken into account by writers who wish to achieve rhetorical ends. Using three case studies of network formation on the microblogging service Twitter, I show how the acts of resonance and switching, along with the protocol and program of these networks, influence network formation, the types of communication generated by networks, and how those networks are received by outsiders. / text

Social media have been growing rapidly in recent years thanks to the innovations of social networking sites (SNS) such as Facebook and Twitter, both of which originated in the United States. Currently, SNS and other social media have become global phenomena. This report aims to study the features of SNS that prosper in the U.S., Japan, and China. Through a comparative analysis of the similarities and differences among the top SNS players in each of the three countries, it is possible to identify unique characteristics of each nation’s social networking landscape. The SNS market in the U.S. is relatively mature, while the social networking population is growing in Japan and China. However, contrary to the expectations of some, the Japanese and Chinese social networking landscapes appear to be quite different from one another with regard to SNS usage, despite Japan and China’s similar cultural backgrounds and geographical proximity. / text

This thesis investigates automatic geolocation (i.e. identification of the location, expressed as latitude/longitude coordinates) of documents. Geolocation can be an effective means of summarizing large document collections and is an important component of geographic information retrieval. We describe several simple supervised methods for document geolocation using only the document’s raw text as evidence. All of our methods predict locations in the context of geodesic grids of varying degrees of resolution. We evaluate the methods on geotagged Wikipedia articles and Twitter feeds. For Wikipedia, our best method obtains a median prediction error of just 11.8 kilometers. Twitter geolocation is more challenging: we obtain a median error of 479 km, an improvement on previous results for the dataset. / text

This dissertation addresses the rhetoric of deficiency that frames Latina/o students as lacking with regard to education. This dissertation begins by examining the cultural deficit model entrenched in colonial narratives of history that justify unequal access to resources in the US. I argue that the reimagining of the pejorative trope of 'pocho' by reconnecting it with its etymological root pochteca provides a trope of resistance to deficiency rhetoric, and a trope that embodies rhetorical strategies for Latina/o students navigating academic institutions. Additionally, this dissertation furthers the advocacy of culturally relevant reading and writing assignments and practices, while at the same time arguing that the discursive productions responding to culturally relevant writing demonstrate rhetorical strategies. The analysis of a student publication that responds to and integrates dichos provides a site of analysis where students identify rhetorical strategies that help them navigate obstacles related to education. The use of Twitter by a predominantly Latina/o summer bridge program provides an additional site of analysis where the writing of students in digital spaces allows them to perform latinidad, and create support networks that help them succeed in school. The pedagogical chapter of this dissertation analyzes the Arizona House Bill 2281 and the rhetoric that frames the Tucson Unified School District's Mexican American Studies program as racist and anti-American; following this analysis come suggestions for incorporating culturally relevant aspects of the TUSD MAS curriculum into rhetoric and composition curriculum.

The purpose of this thesis was to study a selection of Swedish government agencies and their usage of new media to convey information. We thought that the relationship between government agencies and the media should be addressed. This because of the current transitional period between traditional and new media. We have studied five different Swedish government agencies; Swedish Armed Forces, Swedish Tax Agency, Swedish National Institute of Public Health, Trafikverket and Sida. We used a qualitive content analysis and analyzed their homepages on the basis of six different criteria. In addition to this we studied their presence on external social communities and how the government agencies comply with the requirements of their communicative efforts. The study shows that the government agencies’ media usage varies. With the homepage as a common ground, the media use of government agencies approaches to using new media. It depends on the individual government agency's specific needs of providing information.

This study examined the effectiveness of social media marketing on college students attending a recreation special event. Facebook and Twitter were assessed via an experimental design. To measure the effectiveness of these applications (through updating statuses) on a college student’s awareness, interest, and intent of attending a special event, three groups were employed (Facebook, Twitter, and Control). A total of 134 participants were recruited via six undergraduate courses and were assigned into three groups based on their social media consumption. Subjects responded to a pre-survey, joined their respective treatment group, and completed a post-survey. Descriptive statistics revealed that awareness increased for those who received Facebook status updates and tweets. The interest level of the treatment groups decreased from the pre to the post-test and the intention of participants to participate increased slightly for the Facebook treatment group, but the intent level of participants in the Twitter and Control groups decreased.

Geo-based Information Visualizations (GIV) allow people to analyze data points based on their related geographic locations. This approach is usually adopted where a large scale geo-referenced dataset is present and users are trying to find a way to examine hidden patterns within this data. One of the emerging trends in GIV is to visualize social media data to show how information flows between users of popular social networking sites. Due to its public nature and the large number of users, most of the visualizations in this area rely on conversational data from Twitter (Twitter.com). In this thesis, we design and implement a web-based interactive GIV system, AcademiaMap-GIV, to visualize online conversations among scholars on Twitter. A formal exploratory user study was also conducted on the target users. The study results demonstrated that most of the study respondents found the features of AcademiaMap-GIV effective in regards to visualizing information of their interests.

This qualitative phenomenological study involving in-depth interviews with seven educators in K-12 and higher education examines the role that the microblogging service Twitter plays in the formation and development of Personal Learning Networks (PLN) among educators. A double hermeneutic data analysis shows that Twitter plays a role in the formation and development of PLNs by allowing educators to; engage in consistent and sustained dialogue with their PLN, access the collective knowledge of their PLN, amplify and promote more complex thoughts and ideas to a large audience, and expand their PLN using features unique to Twitter. This research also examines the nature of a PLN and shows that participants believe their PLN extends beyond their Twitter network to encompass both face-to-face and other ICT mediated relationships. Secondary research questions examine how Twitter differs from other social networking tools in mediating relationships within a PLN, what motivates an educator to develop a PLN, how trust is established in a PLN, what the expectations of reciprocity are within a PLN, and what is the nature of informal learning within a PLN. Keywords: Twitter, microblogging, Personal Learning Network, PLN, informal learning

Many large-scale social systems such as Web-based social networks, online social media sites and Web-scale crowdsourcing systems have been growing rapidly, enabling millions of human participants to generate, share and consume content on a massive scale. This reliance on users can lead to many positive effects, including large-scale growth in the size and content in the community, bottom-up discovery of “citizen-experts”, serendipitous discovery of new resources beyond the scope of the system designers, and new social-based information search and retrieval algorithms. But the relative openness and reliance on users coupled with the widespread interest and growth of these social systems carries risks and raises growing concerns over the quality of information in these systems. In this dissertation research, we focus on countering threats to the quality of information in self-managing social systems. Concretely, we identify three classes of threats to these systems: (i) content pollution by social spammers, (ii) coordinated campaigns for strategic manipulation, and (iii) threats to collective attention. To combat these threats, we propose three inter-related methods for detecting evidence of these threats, mitigating their impact, and improving the quality of information in social systems. We augment this three-fold defense with an exploration of their origins in “crowdturfing” – a sinister counterpart to the enormous positive opportunities of crowdsourcing. In particular, this dissertation research makes four unique contributions: • The first contribution of this dissertation research is a framework for detecting and filtering social spammers and content polluters in social systems. To detect and filter individual social spammers and content polluters, we propose and evaluate a novel social honeypot-based approach. • Second, we present a set of methods and algorithms for detecting coordinated campaigns in large-scale social systems. We propose and evaluate a content- driven framework for effectively linking free text posts with common “talking points” and extracting campaigns from large-scale social systems. • Third, we present a dual study of the robustness of social systems to collective attention threats through both a data-driven modeling approach and deploy- ment over a real system trace. We evaluate the effectiveness of countermeasures deployed based on the first moments of a bursting phenomenon in a real system. • Finally, we study the underlying ecosystem of crowdturfing for engaging in each of the three threat types. We present a framework for “pulling back the curtain” on crowdturfers to reveal their underlying ecosystem on both crowdsourcing sites and social media.

A method has been developed to track infectious diseases by using data mining of active Twitter accounts and its efficacy was demonstrated during the West African Ebola outbreak of 2014. Using a meme based n-gram semantic usage model to search the Twitter database for indications of illness, flight and death from the spread of Ebola in Africa, principally from Guinea, Sierra Leone and Liberia. Memes of interest relate disease to location and severity and are coupled to the density of Tweets and re-Tweets. The meme spreads through the community of social users in a fashion similar to nonlinear wave propagation- like a shock wave, visualized as a spike in Tweet activity. The spreading was modeled as a system isomorphic to a modified SIR (Susceptible, Infected, Removed disease model) system of three coupled nonlinear differential equations using Twitter variables. The nonlinear terms in this model lead to feedback mechanisms that result in unusual behavior that does not always reduce the spread of the disease. The resulting geographic Tweet densities are coupled to geographic maps of the region. These maps have specific threat levels that are ported to a mobile application (app) and can be used by travelers to assess the relative safety of the region they will be in.