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                  <text>VOL 28 ISSUE 5 2023</text>
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                <text>To intervene or not to intervene: young adults’ views on&#13;
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                <text>social networking sites, online communities, qualitative methods, young adults, bystanders</text>
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                <text>Incidents of online harassment are increasing and can have significant consequences for victims. Witnesses (“digital bystanders”) can be crucial&#13;
in identifying and challenging harassment. This study considered when and how young adults intervene online, with the aim of understanding&#13;
the applicability of existing theoretical models (i.e., Bystander Intervention Model; Response Decision-Making Framework). Thematic analysis of&#13;
eight focus groups (UK community sample, N 1⁄4 67, 18–25 years) resulted in five themes: Noticing and Interpreting the Harassment, Perceived&#13;
Responsibility for Helping, Consequences of Intervening, Perceived Ability to Make a Difference, and Deciding How to Help. The online context&#13;
&#13;
amplified offline preferences, such as greater preference for anonymity and perceived costs of intervention (e.g., social costs). Intervention strat-&#13;
egies varied in visibility and effort, preferring “indirect” micro-interventions focused on supporting victims. A new, merged model specific to digi-&#13;
tal bystanders is proposed, with implications for the design and messaging on social networking sites discussed.</text>
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                <text>Anna Davidovic1,*, Catherine Talbot 2&#13;
&#13;
, Catherine Hamilton-Giachritsis3&#13;
&#13;
, Adam Joinson1</text>
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                <text>https://doi.org/10.1093/jcmc/zmad027</text>
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                <text>Attitudinal and behavioral correlates of algorithmic&#13;
awareness among German and U.S. social media users</text>
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                <text>algorithmic literacy, algorithmic awareness, algorithmic attitudes, algorithmic divide, social media algorithms</text>
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                <text>With the increase in algorithms on social media, scholarship is increasingly focused on “algorithmic literacy,” or users’ understanding of&#13;
algorithms. Algorithmic literacy is multi-faceted (knowledge, attitudes, and behavior), and researchers are still uncovering how these facets are&#13;
connected. This article presents a preregistered survey of social media users from two western countries: the United States (n 1⁄4 990) and&#13;
Germany (n 1⁄4 1117). Results show key predictors of algorithmic awareness—age, education, frequency of social media use—are the same in&#13;
both countries. Nevertheless, U.S. social media users show higher algorithmic awareness and more positive attitudes toward algorithms than&#13;
German social media users, likely due to their higher overall social media usage. Results also indicate that algorithmic awareness predicts&#13;
attitudes about filtering algorithms depending on users’ defense motivations or accuracy motivations and behaviors to counteract filtering. These&#13;
patterns have implications for literacy interventions and for increasing algorithmic transparency.</text>
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                <text>Anne Oeldorf-Hirsch 1,*, German Neubaum</text>
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                <text>https://doi.org/10.1093/jcmc/zmad035</text>
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                <text>PERI IRAWAN</text>
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                  <text>VOL 28 ISSUE 5 2023</text>
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                <text>No judgment: value optimization and the reinvention of&#13;
reviewing on YouTube</text>
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                <text>creators, evaluation, platforms, platformized cultural production, optimization, reviews, values, YouTube</text>
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                <text>Social media platforms employ algorithmic recommendations to optimize the user’s experience and incentivize particular forms of cultural pro-&#13;
duction. While prior research shows that creators respond to these incentives and seek to optimize their content in return, the normative implica-&#13;
tions of this process are ambiguous and contentious. To examine the values promoted by platforms, this study focuses on YouTube reviews, a&#13;
&#13;
popular genre that crosses communities and foregrounds values. Employing content and thematic analyses of 200 videos, I find that creators&#13;
communicate value consistently: good products are aesthetic, functional, distinctive, and either pleasurable or resonant, while good reviewers&#13;
are relatable above all else. I develop the concept of value optimization to refer to communicative strategies that appeal to the perceived values&#13;
of a platform and show how creators’ tendency to qualify their evaluations and avoid strong judgments transforms the historical function of&#13;
reviewing. Finally, I discuss implications for future research on the platformization of cultural production.</text>
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                <text>Blake Hallinan</text>
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                <text>https://doi.org/10.1093/jcmc/zmad034</text>
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                  <text>VOL 28 ISSUE 5 2023</text>
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    <elementSetContainer>
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          <element elementId="50">
            <name>Title</name>
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                <text>Communication about sensors and communication&#13;
through sensors: localizing the Internet of Things in rural&#13;
communities</text>
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          <element elementId="49">
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            <description>The topic of the resource</description>
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                <text>Internet of Things, technology adoption, urban/rural, community, qualitative methods, smart homes/cities</text>
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                <text>Internet of Things (IoT) sensor networks are an emerging technology at the center of the datafication and optimization of far-reaching environmental&#13;
infrastructures—from “smart cities” to workplace efficiencies. However, this low-power, low-cost technology is also well suited to local deployments&#13;
in rural communities, which are often overlooked by digital development initiatives. Therefore, we used a social construction of technology approach to&#13;
&#13;
study how various U.S.-based IoT stakeholders—including designers and advocates as well as citizen stakeholders—understand and value sensor net-&#13;
work technologies. Through observational methods, in-depth interviews, and participatory design research in a rural Upstate New York municipality,&#13;
&#13;
we worked to design sensor networks with rural community members to generate data about and for community members to further local&#13;
knowledge. We found that designing rural sensor networks requires stakeholders to navigate obstacles of communication about sensors and&#13;
communication through sensors to facilitate secure, ethical, and localized sensing in rural communities.</text>
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                <text>Chelsea Butkowski 1,*, Ngai Keung Chan2&#13;
&#13;
, Talia Berniker3&#13;
&#13;
, Alfredo Rodriguez4&#13;
,&#13;
&#13;
Kenneth Schlather5&#13;
&#13;
, K. Max Zhang4&#13;
&#13;
, Lee Humphreys</text>
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                <text>https://doi.org/10.1093/jcmc/zmad005</text>
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                <text>10 February 2023</text>
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                <text>PERI IRAWAN</text>
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            <description>A language of the resource</description>
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                <text>ENGLISH</text>
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                  <text>VOL 28 ISSUE 5 2023</text>
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                <text>Negotiating the capacities and limitations of&#13;
sensor-mediated care in the home</text>
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                <text>sensor, healthcare, infrastructure, dementia, labor, ethics</text>
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                <text>In-home sensor systems supported by machine learning are increasingly used to enhance communication between those living with long-term&#13;
conditions such as dementia and healthcare professionals and carers who support them. Perspectives from the sociology of infrastructures are&#13;
used to explore the development and deployment of such a system of smart care, drawing on interviews with researchers and developers,&#13;
healthcare professionals and service users, and carers. The analysis finds that labor of various forms is required to manage the production of&#13;
useful sensor data, including parsing the reasons for missing data and organizing appropriate actions in response. The analysis highlights active&#13;
processes of deriving meaning from that data in ways that participants find useful, ethical, and sustainable. The conclusion emphasizes the&#13;
usefulness of an infrastructural approach in order to recognize the heterogeneous forms of labor involved in developing ethically sensitive,&#13;
person-centered forms of remote-monitoring-enabled care.</text>
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                <text>Christine Hine 1,*, Ramin Nilforooshan2&#13;
&#13;
, Payam Barnaghi3</text>
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&#13;
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&#13;
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&#13;
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,&#13;
&#13;
Michael D. Schmidt5&#13;
&#13;
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&#13;
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                <text>self-tracking, sensors, domestic labor, productivity, home–workplace separation, neoliberal/digital capitalism, gender</text>
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                <text>This article explores how women in Turkey use sensing technologies to render visible their productivity at home in ways that contest home–&#13;
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&#13;
home as both paid laborers and unpaid caregivers. Although neoliberalism makes it harder to distinguish home and workplace, my digital ethnog-&#13;
raphy highlights that women working from home feel a home–workplace separation that renders invisible their productivity. By translating em-&#13;
bodied knowledge into quantified data, smartwatches provide women with new information that I call revelations. Women share these revela-&#13;
tions on digital platforms to render visible their productivity at home in ways that transgress the home–workplace boundary. By exploring these&#13;
&#13;
revelations as moments of “otherwise,” this article highlights both when smartwatches reproduce neoliberal mentality and become tools for&#13;
others in the public to register its exploitative consequences.</text>
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                <text>Nazlı O ̈ zkan1,*</text>
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&#13;
parents that reflected the composition of the U.S. population to explore how parents’ resources and digital parenting readiness predict their digi-&#13;
tal mediation strategies. The results indicate that parents’ economic, social, and cultural resources, as well as their digital parenting readiness,&#13;
&#13;
play a significant role in how they approach digital mediation. Furthermore, digital parenting readiness has emerged as an underlying mechanism&#13;
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          <element elementId="50">
            <name>Title</name>
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                <text>Sensor work: enabling the interoperation of&#13;
autonomous vehicles</text>
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          <element elementId="49">
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                <text>sensing, autonomous driving, interoperability, sensor work, machine vision, AI</text>
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                <text>This article examines the “sensor work” carried out in the development of autonomous vehicles which, without sensor data, would not and&#13;
arguably still do not, have the capacity to decide on where, and how, to drive. I begin by discussing three aspects of sensor technologies&#13;
considered to be the foundation for sensor work being carried out in autonomous vehicle settings, namely the distribution, processing, and&#13;
sourcing of sensor technologies and sensor data. The article considers how that much of this sensor work aids not only the operation of&#13;
autonomous vehicles but also their necessary “interoperation.” In studying four specific sensing methods from an operational perspective,&#13;
I consider how the interoperation between sensing devices and subsequent algorithmic, object-recognition, and motion planning procedures is&#13;
fundamental to the development of autonomous vehicles.</text>
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                <text>Sam Hind</text>
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                <text>https://doi.org/10.1093/jcmc/zmad014</text>
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                <text>Oxford University Press on behalf of International Communication Association.</text>
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                <text>5 April 2023</text>
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                <text>PERI IRAWAN</text>
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                <text>PDF</text>
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