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                  <text>VOL 29 ISSUE 4 2024</text>
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                <text>Inspiring or demoralizing? Deservingness perceptions help&#13;
determine why emerging adults experience positive or&#13;
negative effects from envy-inducing social media posts</text>
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                <text>social comparison, social media, benign envy, malicious envy, Instagram, college success.</text>
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                <text>This study extends pain-driven dual envy theory to explain why emerging adults who do not attend college might experience uplifting or hostile&#13;
reactions to the social media posts of their college-attending peers. Employing a 2 × 2 experiment (N 1⁄4 233; Mage 1⁄4 21.87), we examined how&#13;
deservingness perceptions (deserving versus undeserving) and social approval cues (high versus low) affect the type of envy emerging adults&#13;
experience from viewing college success posts on social media. Results indicated that the more participants perceived the college success of&#13;
their peers to be deserved, the more they experienced benign envy. Conversely, the more participants appraised the college success of their&#13;
&#13;
peers to be undeserved, the more they experienced malicious envy. Results also indicated that posts with higher social approval indirectly trig-&#13;
gered more pain for participants. Overall, findings help clarify why social media users can experience both positive and negative effects from on-&#13;
line social comparisons.</text>
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                <text>Enoch Montes1,�, David C. DeAndrea</text>
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                <text>https://doi.org/10.1093/jcmc/zmae006</text>
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                <text>Oxford University Press on behalf of International Communication Association.</text>
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                <text>May 16, 2024</text>
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                <text>Accumulative cartography: a visual semiotic analysis of&#13;
online mobile maps</text>
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                <text>dynamic maps, navigation apps, visual semiotics, walk-through method, user interface design.</text>
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                <text>Dynamic maps featured in navigation applications draw on conventional cartographic practices for representing the urban environment, engag-&#13;
ing drivers and users of public transportation in their efforts to reach their destinations. However, since these maps are produced within an&#13;
&#13;
economy of data accumulation, their construction of territory and user-friendly interface are designed to generate value. In this article, we ex-&#13;
plore what we define as accumulative cartography—mapping designed for the accumulation of data and capital—by developing a semiotic&#13;
&#13;
walk-through method for analyzing dynamic maps. Our visual semiotic analysis of Waze, Moovit, and Gett reveals that their maps are personal-&#13;
ized, centering on the user; they commodify space, aiming to promote their specific business models; and they are preoccupied with time. We&#13;
&#13;
suggest that in contrast to printed maps, dynamic maps don’t provide users with the information required for navigation but instead navigate al-&#13;
gorithmically for them, while accumulating their information.</text>
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                <text>Igal Baum1&#13;
&#13;
, Rivka Ribak</text>
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                <text>https://doi.org/10.1093/jcmc/zmae009</text>
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                <text>Oxford University Press on behalf of International Communication Association.</text>
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                <text>June 14, 2024</text>
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                <text>Enacting machine agency when AI makes one’s&#13;
day: understanding how users relate to AI communication&#13;
technologies for scheduling</text>
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                <text>artificial intelligence, agency, machine agency, structuration theory, AI-mediated communication.</text>
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                <text>AI Communication Technologies (AICTs) make decisions about users’ communication on their behalf. Users’ implementation of AICTs that au-&#13;
tonomously act may enable and constrain how they accomplish their work and interact with others. Drawing on interviews with users of two&#13;
&#13;
AICTs with differing levels of autonomy designed for work-related scheduling, this study investigated how users enacted AICTs in practice.&#13;
Users of both tools drew on AICTs’ autonomous capabilities to enact machine agency, a structure that assigns AICTs the power to allocate&#13;
resources, which helped them increase scheduling efficiency and guide how others interacted with them. Users of the tool that autonomously&#13;
implemented decisions described a process of enactment in which they used the tool to control their work, perceived the tool was exhibiting&#13;
too much control, and acted to regain control. I present implications for understanding how people enact machine agency with AICTs that make&#13;
decisions about their work.</text>
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                <text>Camille G. Endacott PhD,1,�</text>
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                <text>https://doi.org/10.1093/jcmc/zmae011</text>
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