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                <text>Correction&#13;
Correction to: Social Media Browsing and Adolescent Well-Being: Challenging the “Passive&#13;
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                <text>This is a correction to: Patti M Valkenburg, Ine Beyens, J Loes</text>
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                <text>This is a correction to: Patti M Valkenburg, Ine Beyens, J Loes&#13;
Pouwels, Irene I van Driel, Loes Keijsers, Social Media&#13;
Browsing and Adolescent Well-Being: Challenging the “Passive&#13;
Social Media Use Hypothesis”, Journal of Computer-Mediated&#13;
Communication, Volume 27, Issue 1, January 2022, zmab015,&#13;
https://doi.org/10.1093/jcmc/zmab015&#13;
&#13;
In the published version of this article, the supplementary&#13;
&#13;
files were inadvertently omitted. In order to preserve the ver-&#13;
sion of record, these files have not been added to the original&#13;
&#13;
article but are being made available with this correc-&#13;
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                <text>It matters how you google it? Using agent-based testing to&#13;
assess the impact of user choices in search queries and&#13;
algorithmic personalization on political Google Search results&#13;
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                <text>search engines, political information, search queries, user choice, algorithmic personalization.</text>
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                <text>Search engines, as key sources of political information, have sparked concerns regarding selective exposure driven by user choices based on&#13;
political beliefs and filter bubbles created by algorithms. This study focuses on the most influential yet often-overlooked user choice: search&#13;
queries. We investigate the extent to which user choices (search queries) and algorithmic personalization (search history) lead to divergent&#13;
&#13;
search results. Building on research linking immigration- and climate-related search queries to political characteristics, we conduct an experi-&#13;
ment on Google Search employing agent-based testing. Using computational methods, we examine variations in search results by source (type)&#13;
&#13;
and search result page features. Our findings show that it is the specific search queries made by users, not algorithmic personalization, that&#13;
lead to substantially divergent information sources in search results. This suggests future research should prioritize user choices in information&#13;
search rather than control for them.</text>
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                <text>Marieke van Hoof 1,�, Damian Trilling 2&#13;
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&#13;
, Corine S. Meppelink</text>
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                <text>https://doi.org/10.1093/jcmc/zmae020</text>
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                <text>Oxford University Press on behalf of International Communication Association.</text>
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                <text>Machine heuristic: concept explication and development of&#13;
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                <text>machine heuristic, cognitive heuristic, concept explication, scale development, scale validation.</text>
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                <text>Human assumption of superior performance by machines has a long history, resulting in the concept of “machine heuristic” (MH), which is a&#13;
mental shortcut that individuals apply to automated systems. This article provides a formal explication of this concept and develops a new scale&#13;
based on three studies (Combined N 1⁄4 1129). Measurement items were derived from the explication and an open-ended survey (Study 1,&#13;
N 1⁄4 270). These were then administered in a closed-ended survey (Study 2, N 1⁄4 448) to identify their dimensionality through exploratory factor&#13;
&#13;
analysis (EFA). Lastly, we conducted another survey (Study 3, N 1⁄4 411) to verify the factor structure obtained in Study 2 by employing confirma-&#13;
tory factor analysis (CFA). Analyses resulted in a validated scale of seven items that reflect the level of MH in individuals and identified six sets&#13;
&#13;
of descriptive labels for machines (expert, efficient, rigid, superfluous, fair, and complex) that serve as formative indicators of MH. Theoretical&#13;
and practical implications are discussed.</text>
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                <text>Hyun Yang 1,�, S. Shyam Sundar</text>
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                <text>https://doi.org/10.1093/jcmc/zmae019</text>
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                <text>Oxford University Press on behalf of International Communication Association.</text>
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                <text>Topic territoriality and the cost of civility: examining the&#13;
impact of IP address disclosure on Weibo</text>
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                <text>topic territoriality, intergroup communication, psychological ownership, identity cues, toxicity.</text>
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                <text>This article introduces the concept of “topic territoriality,” a mechanism that governs participation in conversational spaces. When a discussion&#13;
becomes prone to territorialization, individuals are more likely to claim topics (participating in discussions about topics they own as&#13;
“stakeholders”) and defer (reducing participation in topics owned by others). They are also more likely to patrol topic boundaries (monitoring&#13;
who is participating and confronting topic “intruders”). We document the operation of topic territoriality by analyzing 112,278 conversational&#13;
turns on Weibo before and after a policy that reveals users’ broad geographic locations. We find that revealing these locations increased&#13;
territorial behaviors, leading to more homogenous participation in conversations. Although the display of locations has improved the overall&#13;
civility in language, the confrontations between stakeholders and intruders became more toxic. Our research emphasizes the impact of topic&#13;
territoriality in online conversations and sheds light on the unintended consequences of social media policies.</text>
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                <text>Chao Yu 1,�, Drew Margolin</text>
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                <text>https://doi.org/10.1093/jcmc/zmae018</text>
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                <text>August 12, 2024</text>
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