1,720,973 research outputs found
Searching for Community Online: How Virtual Spaces Affect Student Notions of Community
Get PDFSocial networking sites and virtual spaces have flourished in the past few years. The author explores the impact of such social networking services on the local community at a small liberal arts college. The author investigates modern trends in community theory. Defining community has become more difficult in modern society, where community is no longer easily distinguished by geographical boundaries. From the background of modern community theory the author explores the designation of virtual spaces as “virtual communities.” Literature and research about virtual spaces indicates that they can provide many of the values thought be to inherent to community membership. The strong localized community on campus makes students hesitant in calling Facebook a “virtual community,” despite its strong integration with the face-to-face community itself. Facebook is seen as simply a tool. This thesis incorporates research on one specific case study: through mathematical and ethnographic research of Facebook.com, the author evaluates the opinions of students in considering virtual spaces as communities
The Future of AI Can Be Kind: Strategies for Embedded Ethics in AI Education
No full textThesis (Ph.D.)--University of Washington, 2024The field of Data Science has seen rapid growth over the past two decades, with a high demandfor people with skills in data analytics, programming, statistics, and ability to visualize, predict
from, and otherwise make sense of data. Alongside the rise of various artificial intelligence
(AI) and machine learning (ML) applications, we have also witnessed egregious algorithmic
biases and harms – from discriminatory outputs of models to reinforcing normative ideals about
beauty, gender, race, class, etc. These harms range from high profile cases such as the racial
bias embedded in the COMPAS recidivism algorithm, to more insidious cases of algorithmic
harm that compound over time with re-traumatizing effects (such as the mental health impacts
of recommender systems, social media content organization and the struggle for visibility, and
discriminatory content moderation of marginalized individuals [400, 401]). There are various
strategies to combat and repair algorithmic harms, ranging from algorithmic audits and fairness
metrics to AI Ethics Standards put forth by major institutions and tech companies. However,
there is evidence to suggest that current Data Science curricula do not adequately prepare
future practitioners to effectively respond to issues of algorithmic harm, especially the day-to-
day issues that practitioners are likely to face. Through a review of AI Ethics standards and
the literature, I devise a set of 9 characterizations of effective AI ethics education: specific,
prescriptivist, action-centered, relatable, empathetic, contextual, expansive, preventative, and
integrated. The empirical work of this dissertation reveals the value of embedding ethical critique
into technical machine learning instruction – demonstrating how teaching AI concepts using
cases of algorithmic harm can boost both technical comprehension and ethical considerations
[397, 398]. I demonstrate the value of relying on real-world cases and experiences that students
already have (such as with hiring/admissions decisions, social media algorithms, or generative AI
tools) to boost their learning of both technical and social impact topics. I explore this relationship
between personal relatability and experiential learning, demonstrating how to harness students’
lived experiences to relate to cases of algorithmic harm and opportunities for repair. My
preliminary work also reveals significant in-group favoritism, suggesting students find AI errors
more urgent when they personally relate to them. While this may prove beneficial for engaging
underrepresented students in the classroom, it must be paired with empathy-building techniques
for students who relate less to cases of algorithmic harm, as well as trauma-informed pedagogical
practice. My results also revealed an over-reliance on “life-or-death reasoning” when it came to
ethical decision-making, along with organizational and financial pressures that might impede AI
professionals from delaying harmful software. This dissertation contributes several strategies
to effectively prepare Data Scientists to consider both technical and social aspects of their work,
along with empirical results suggesting the benefits of embedded ethics throughout all areas of
AI education
United We Tweet?: A Quantitative Analysis of Racial Differences in Twitter Use
No full textThesis (Ph.D.)--University of Washington, 2017This study is grounded in the perspective that individuals who use Twitter exist within a racialized social structure, and that if handed a flexible platform for communication they may establish different patterns of use. It acknowledges Twitter as a novel social context in which users co-create meaning and structure, and is informed by theory addressing the role of race and racial identity within both online and offline spaces. Chapters analyze black-white racial variation in self-presentation, site use, and network formation using digital traces from two datasets of Twitter of users in the United States. Results indicate that while Twitter is in many ways a race-neutral context, black users are less likely to disclose personal identity indicators, tend to tweet at others less frequently and with a smaller volume of personal ties, and often have higher levels of racial homophily within their networks than white users. White users are more outwardly vocal, more likely to disclose personal identity indicators, and more likely to engage with Twitter as an information space. Overall, Twitter appears not to be immune to the influence of offline biases and identities, and there are some black users for whom the narrative of Black Twitter – or Twitter as a community building space – may hold true
The Measurement and Representation of Influencer Communities in United States Political Discourse on Social Media
No full textThesis (Ph.D.)--University of Washington, 2024The United States (U.S.) is in the midst of a paradigm shift in who creates news. It is widely known that the internet has in the past few decades displaced television and print newspapers as the primary medium where news is consumed. However, the past two decades have also seen a shift in who is communicating the news. People consuming digital news, and especially young people, are now less likely than they were to get their news from journalists or television broadcasters, and more likely to receive it from a nebulous figure commonly referred to as the influencer. People are not only paying more attention to influencers, but there has seemingly been a remarkable growth in the type of and number of influencers in the last decade. This growth has been enabled both by the maturation of new, massively-networked social media platforms and the industrialization of influencing as a profession and an economic infrastructure. In this dissertation, I use quantitative and qualitative methods to analyze case studies of U.S. political discourse networks to better understand the structure, tactics, and consequences of our new era of influencer media. After conducting a literature review of previous work on influencers in political communication and media studies, I propose flexible ways to represent both influencers and what I call influencer communities in social media networks. Influencer communities are assemblages of influencers working cooperatively and antagonistically to earn the attention of networked audiences on large social media platforms. Via four case studies of Twitter discourse in the U.S., each of which presents a new method for understanding influencers' behaviors and organization, I seek to understand how to represent and visualize influencer communities; how to analyze the strategies that influencers pursue within these communities; and how to understand the effects these influencer communities have on political discourse in the United States. I conclude this dissertation with a collection of reflections, most of which concern how characteristics of influencer communities, such as their embeddedness in power relations and their relationship to the "mainstream," structure which strategies influencers within them take
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
- …
