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    <dc:date>2026-04-28T10:14:57Z</dc:date>
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    <title>AI images, labels and news demand</title>
    <link>https://hdl.handle.net/10419/336444</link>
    <description>Title: AI images, labels and news demand
Authors: Adena, Maja; Alabrese, Eleonora; Capozza, Francesco; Leader, Isabelle
Abstract: We test whether AI-generated news images affect outlet demand and trust. In a preregistered experiment with 2,870 UK adults, the same article was paired with a wireservice photo (with/without credit) or a matched AI image (with/without label). Average newsletter demand changes little. Ex-post photo origin recollection is poor, and many believe even the real photo is synthetic. Beliefs drive behavior: thinking the image is AI cuts demand and perceived outlet quality by about 10 p.p., even when the photo is authentic; believing it is real has the opposite effect. Labels modestly reduce penalties but do little to correct mistaken attributions.</description>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
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  <item rdf:about="https://hdl.handle.net/10419/336445">
    <title>The impact of behavioral design and users' choice on smartphone app usage and willingness to pay: A framed field experiment</title>
    <link>https://hdl.handle.net/10419/336445</link>
    <description>Title: The impact of behavioral design and users' choice on smartphone app usage and willingness to pay: A framed field experiment
Authors: Timko, Christina; Adena, Maja
Abstract: Behavioral design in smartphone apps aims at inducing certain, monetizable behavior, mainly increased engagement, measurable by usage time. Such design is rarely transparent and often restricts users' ability to make alternative choices. In a framed field experiment, we document that behavioral design doubles app usage time compared to a version without behavioral elements. Providing users with choices-simply explained and conveniently adjustable design features-reduces usage time and increases their willingness to pay for the app. These findings suggest that offering choice could pave the way for new business models based on more responsible app design.</description>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
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    <title>Politicized scientists: Credibility cost of political expression on Twitter</title>
    <link>https://hdl.handle.net/10419/336443</link>
    <description>Title: Politicized scientists: Credibility cost of political expression on Twitter
Authors: Alabrese, Eleonora; Capozza, Francesco; Garg, Prashant
Abstract: As social media becomes prominent within academia, we examine its reputational costs for academics. Analyzing Twitter posts from 98,000 scientists (2016-22), we uncover substantial political expression. Online experiments with 4,000 U.S. respondents and 135 journalists, rating synthetic academic profiles with different political affiliations, reveal that politically neutral scientists are seen as the most credible. Strikingly, political expressions result in monotonic penalties: Stronger posts more greatly reduce the perceived credibility of scientists and their research and audience engagement, particularly among oppositely aligned respondents. Two surveys with scientists highlight their awareness of penalties, their perceived benefits, and a consensus on limiting political expression outside their expertise.</description>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
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