48 research outputs found
Searching for Community Online: How Virtual Spaces Affect Student Notions of Community
Social 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
Networks of Gratitude: Structures of Thanks and User Expectations in Workplace Appreciation Systems
Appreciation systems--platforms for users to exchange thanks and praise--are
becoming common in the workplace, where employees share appreciation, managers
are notified, and aggregate scores are sometimes made visible. Who do people
thank on these systems, and what do they expect from each other and their
managers? After introducing the design affordances of 13 appreciation systems,
we discuss a system we call Gratia, in use at a large multinational company for
over four years. Using logs of 422,000 appreciation messages and user surveys,
we explore the social dynamics of use and ask if use of the system addresses
the recognition problem. We find that while thanks is mostly exchanged among
employees at the same level and different parts of the company, addressing the
recognition problem, managers do not always act on that recognition in ways
that employees expect.Comment: in Tenth International AAAI Conference on Web and Social Media, 201
Followback Clusters, Satellite Audiences, and Bridge Nodes: Coengagement Networks for the 2020 US Election
The 2020 United States presidential election was, and has continued to be,
the focus of pervasive and persistent mis- and disinformation spreading through
our media ecosystems, including social media. This event has driven the
collection and analysis of large, directed social network datasets, but such
datasets can resist intuitive understanding. In such large datasets, the
overwhelming number of nodes and edges present in typical representations
create visual artifacts, such as densely overlapping edges and tightly-packed
formations of low-degree nodes, which obscure many features of more practical
interest. We apply a method, coengagement transformations, to convert such
networks of social data into tractable images. Intuitively, this approach
allows for parameterized network visualizations that make shared audiences of
engaged viewers salient to viewers. Using the interpretative capabilities of
this method, we perform an extensive case study of the 2020 United States
presidential election on Twitter, contributing an empirical analysis of
coengagement. By creating and contrasting different networks at different
parameter sets, we define and characterize several structures in this discourse
network, including bridging accounts, satellite audiences, and followback
communities. We discuss the importance and implications of these empirical
network features in this context. In addition, we release open-source code for
creating coengagement networks from Twitter and other structured interaction
data.Comment: Accepted for publication at ICWSM '2
Let's Workout! Exploring Social Exercise in an Online Fitness Community
Increasing attention has been paid to promoting certain healthy habits through social interaction in online communities. At the intersection of social media and activity tracking applications, these platforms capture information on physical activities as well as peer-to-peer interactions. Importantly, they also offer researchers a novel opportunity to understand health behaviors by utilizing the large-scale behavioral trace data they archive. In this study we explore the characteristics and dynamics of social exercise (i.e. fitness activities with at least one peer physically co-present) using data collected from an online fitness community popular with cyclists and runners. In particular, we ask if factors such as temporal seasonality, activity performance and social feedback vary by the number of people participating in an activity; we do so by comparing associations for both men and women. Our results indicate that when peers are physically co-present for fitness activities (i.e. group workouts), exercise tends to be more intense and receive more feedback from other users, across both genders. Findings also suggest gender differences in the observed tendency to complete activities with others. These results have important implications for health and wellness interventions
Using Facebook Data to Examine Culture and Self-Disclosure Behaviors
In this work-in-progress poster, we examine the relationship between societal variables, including cultural attributes, and users' self-disclosure on Facebook. To accomplish this we use a dataset of 425,000 Facebook users who designated a national or regional network. Drawing on both standard demographic control variables and the GLOBE cultural dimensions, we execute an exhaustive model search. The best-performing model confirms our hypotheses about cultural variables, but some of our hypotheses about demographic controls are negated. Consequently, we discuss directions in which to continue our research.ye
SN 2009ip at late times - an interacting transient at+2 years
We present photometric and spectroscopic observations of the interacting transient SN 2009ip taken during the 2013 and 2014 observing seasons. We characterize the photometric evolution as a steady and smooth decline in all bands, with a decline rate that is slower than expected for a solely Co-56-powered supernova at late phases. No further outbursts or eruptions were seen over a two year period from 2012 December until 2014 December. SN 2009ip remains brighter than its historic minimum from pre-discovery images. Spectroscopically, SN 2009ip continues to be dominated by strong, narrow (less than or similar to 2000 km s(-1)) emission lines of H, He, Ca, and Fe. While we make tenuous detections of [Fe II] lambda 7155 and [O I] lambda lambda 6300, 6364 lines at the end of 2013 June and the start of 2013 October, respectively, we see no strong broad nebular emission lines that could point to a core-collapse origin. In general, the lines appear relatively symmetric, with the exception of our final spectrum in 2014 May, when we observe the appearance of a redshifted shoulder of emission at +550 km s(-1). The lines are not blueshifted, and we see no significant near-or mid-infrared excess. From the spectroscopic and photometric evolution of SN 2009ip until 820 d after the start of the 2012a event, we still see no conclusive evidence for core-collapse, although whether any such signs could be masked by ongoing interaction is unclear
Recommended from our members
Model International Mobility Convention
While people are as mobile as they ever were in our globalized world, the movement of people across borders lacks global regulation. This leaves many refugees in protracted displacement and many migrants unprotected in irregular and dire situations. Meanwhile, some states have become concerned that their borders have become irrelevant. International mobility—the movement of individuals across borders for any length of time as visitors, students, tourists, labor migrants, entrepreneurs, long-term residents, asylum seekers, or refugees—has no common definition or legal framework. To address this key gap in international law, and the growing gaps in protection and responsibility that are leaving people vulnerable, the "Model International Mobility Convention" proposes a framework for mobility with the goals of reaffirming the existing rights afforded to mobile people (and the corresponding rights and responsibilities of states) as well as expanding those basic rights where warranted. In 213 articles divided over eight chapters, the Convention establishes both the minimum rights afforded to all people who cross state borders as visitors, and the special rights afforded to tourists, students, migrant workers, investors and residents, forced migrants, refugees, migrant victims of trafficking and migrants caught in countries in crisis. Some of these categories are covered by existing international legal regimes. However, in this Convention these groups are for the first time brought together under a single framework. An essential feature of the Convention is that it is cumulative. This means, for the most part, that the chapters build on and add rights to the set of rights afforded to categories of migrants covered by earlier chapters. The Convention contains not only provisions that afford rights to migrants and, to a lesser extent, States (such as the right to decide who can enter and remain in their territory). It also articulates the responsibilities of migrants vis-à -vis States and the rights and responsibilities of different institutions that do not directly respond to a right held by migrants
Minimal in vivo efficacy of iminosugars in a lethal Ebola virus guinea pig model
The antiviral properties of iminosugars have been reported previously in vitro and in small animal models against Ebola virus (EBOV); however, their effects have not been tested in larger animal models such as guinea pigs. We tested the iminosugars N-butyl-deoxynojirimycin (NB-DNJ) and N-(9-methoxynonyl)-1deoxynojirimycin (MON-DNJ) for safety in uninfected animals, and for antiviral efficacy in animals infected with a lethal dose of guinea pig adapted EBOV. 1850 mg/kg/day NB-DNJ and 120 mg/kg/day MON-DNJ administered intravenously, three times daily, caused no adverse effects and were well tolerated. A pilot study treating infected animals three times within an 8 hour period was promising with 1 of 4 infected NB-DNJ treated animals surviving and the remaining three showing improved clinical signs. MON-DNJ showed no protective effects when EBOV-infected guinea pigs were treated. On histopathological examination, animals treated with NB-DNJ had reduced lesion severity in liver and spleen. However, a second study, in which NB-DNJ was administered at equally-spaced 8 hour intervals, could not confirm drug-associated benefits. Neither was any antiviral effect of iminosugars detected in an EBOV glycoprotein pseudotyped virus assay. Overall, this study provides evidence that NB-DNJ and MON-DNJ do not protect guinea pigs from a lethal EBOV-infection at the dose levels and regimens tested. However, the one surviving animal and signs of improvements in three animals of the NB-DNJ treated cohort could indicate that NB-DNJ at these levels may have a marginal beneficial effect. Future work could be focused on the development of more potent iminosugars
Developing Self-Advocacy Skills through Machine Learning Education: The Case of Ad Recommendation on Facebook
Facebook users interact with algorithms every day. These algorithms can perpetuate harm via incongruent targeted ads, echo chambers, or "rabbit hole" recommendations. Education around the machine learning (ML) behind Facebook (FB) can help users to point out algorithmic bias and harm, and advocate for themselves effectively when things go wrong. One algorithm that FB users interact with regularly is User-Based Collaborative Filtering (UB-CF) which provides the basis for ad recommendation. We contribute a novel research approach for teaching users about a commonly used algorithm in machine learning in real-world context -- an instructive web application using real examples built from the user's own FB data on ad interests. The instruction also prompts users to reflect on their interactions with ML systems, specifically Facebook. In a between-subjects design, we tested both Data Science Novices and Experts on the efficacy of the UB-CF instruction. Taking care to highlight the voices of marginalized users, we use the application as a prompt for surfacing potential harms perpetuated by FB ad recommendations, and qualitatively analyze themes of harm and proposed solutions provided by users themselves. The instruction increased comprehension of UB-CF for both groups, and we show that comprehension is associated with mentioning the mechanisms of the algorithm more in advocacy statements, a crucial component of a successful argument. We provide recommendations for increased algorithmic transparency on social media and for including marginalized voices in the conversation of algorithmic harm that are of interest both to social media researchers and ML educators
Shifting Stakes: Understanding the Dynamic Roles of Individuals and Organizations in Social Media Protests.
In this paper we examine two protests characterized by substantial social media presence and distributed participation frameworks via two core questions: what roles did organizations and individuals play, and how did participants' social interactions change over the course of the protests? To answer these questions, we analyzed a large Twitter activity dataset for the #YoSoy132 student uprising in Mexico and Brazil's "bus rebellion." Results indicate that individuals initially took prominence at the protests but faded in importance as the movements dwindled and organizations took over. Regarding the dynamics and structure of the interactions, we found that key time points with unique social structures often map to exogenous events such as coordinated protests in physical locations. Our results have important consequences for the visibility of such social movements and their ability to attract continued participation by individuals and organizations