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Modifiche a "Monetization in online streaming platforms: an exploration of inequalities in twitch.tv"

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Titolo

  • +{"en"=>"Monetization in online streaming platforms: an exploration of inequalities in twitch.tv"}
  • +{"en"=>"Monetization in online streaming platforms: an exploration of inequalities in twitch.tv"}
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Aggiunte
  • +{"en"=>"Monetization in online streaming platforms: an exploration of inequalities in twitch.tv"}
Eliminazioni
Aggiunte
  • +{"en"=>"Monetization in online streaming platforms: an exploration of inequalities in twitch.tv"}

Corpo del testo

  • +["
    Context
    The live streaming platform Twitch underwent in recent years an impressive growth in terms of viewership and content diversity.The platform has been the object of several studies showcasing how streamers monetize their content via a peculiar system centered around para-sociality and community dynamics. Nonetheless, due to scarcity of data, lots is still unknown about the platform-wide relevance of this explanation as well as its effect on inequalities across streamers.
    Hypothesis
    Thanks to the recent availability of data showcasing the top 10,000 streamers revenue between 2019 and 2021, as well as viewership data from different sources, we characterized the popularity and audience monetization dynamics of the platform. Using methods from social physics and econometrics, we analyzed audience building and retention dynamics and linked them to observed inequalities. We found a high level of inequality across the platform, as well as an ability of top streamers to diversify their revenue sources, through audience renewal and diversification in monetization systems. Our results demonstrate that, even if the platform design and affordance favor monetization for smaller creators catering to specific niches, its non-algorithmic design still leaves room for classical choice biases allowing a few streamers to emerge, retain and renew a massive audience.
    Collaboration
    Related dataset URL
    https://participate.indices-culture.eu/assemblies/indicesDatasets/f/163/proposals/188
    Related insights URL
    https://participate.indices-culture.eu/assemblies/hypotheses/f/170/posts/9
    Indicators
    Creator's revenues
    Evaluation
    "]
  • +["<xml><dl class=\"decidim_awesome-custom_fields\" data-generator=\"decidim_awesome\" data-version=\"0.8.3\"><dt name=\"textarea-1635451235315\">Context</dt><dd id=\"textarea-1635451235315\" name=\"textarea\"><div>The live streaming platform Twitch underwent in recent years an impressive growth in terms of viewership and content diversity.The platform has been the object of several studies showcasing how streamers monetize their content via a peculiar system centered around para-sociality and community dynamics. Nonetheless, due to scarcity of data, lots is still unknown about the platform-wide relevance of this explanation as well as its effect on inequalities across streamers.</div></dd><dt name=\"text-1635451312580\">Hypothesis</dt><dd id=\"text-1635451312580\" name=\"text\"><div>Thanks to the recent availability of data showcasing the top 10,000 streamers revenue between 2019 and 2021, as well as viewership data from different sources, we characterized the popularity and audience monetization dynamics of the platform. Using methods from social physics and econometrics, we analyzed audience building and retention dynamics and linked them to observed inequalities. We found a high level of inequality across the platform, as well as an ability of top streamers to diversify their revenue sources, through audience renewal and diversification in monetization systems. Our results demonstrate that, even if the platform design and affordance favor monetization for smaller creators catering to specific niches, its non-algorithmic design still leaves room for classical choice biases allowing a few streamers to emerge, retain and renew a massive audience.</div></dd><dt name=\"text-1635451372562\">Collaboration</dt><dd id=\"text-1635451372562\" name=\"text\"><div></div></dd><dt name=\"text-1635451427513\">Related dataset URL</dt><dd id=\"text-1635451427513\" name=\"text\"><div>https://participate.indices-culture.eu/assemblies/indicesDatasets/f/163/proposals/188</div></dd><dt name=\"textarea-1669973821818-0\">Related insights URL</dt><dd id=\"textarea-1669973821818-0\" name=\"textarea\"><div>https://participate.indices-culture.eu/assemblies/hypotheses/f/170/posts/9</div></dd><dt name=\"textarea-1635451479530\">Indicators</dt><dd id=\"textarea-1635451479530\" name=\"textarea\"><div>Creator's revenues</div></dd><dt name=\"textarea-1635451518445\">Evaluation</dt><dd id=\"textarea-1635451518445\" name=\"textarea\"><div></div></dd></dl></xml>"]
Eliminazioni
Aggiunte
  • +["
    Context
    The live streaming platform Twitch underwent in recent years an impressive growth in terms of viewership and content diversity.The platform has been the object of several studies showcasing how streamers monetize their content via a peculiar system centered around para-sociality and community dynamics. Nonetheless, due to scarcity of data, lots is still unknown about the platform-wide relevance of this explanation as well as its effect on inequalities across streamers.
    Hypothesis
    Thanks to the recent availability of data showcasing the top 10,000 streamers revenue between 2019 and 2021, as well as viewership data from different sources, we characterized the popularity and audience monetization dynamics of the platform. Using methods from social physics and econometrics, we analyzed audience building and retention dynamics and linked them to observed inequalities. We found a high level of inequality across the platform, as well as an ability of top streamers to diversify their revenue sources, through audience renewal and diversification in monetization systems. Our results demonstrate that, even if the platform design and affordance favor monetization for smaller creators catering to specific niches, its non-algorithmic design still leaves room for classical choice biases allowing a few streamers to emerge, retain and renew a massive audience.
    Collaboration
    Related dataset URL
    https://participate.indices-culture.eu/assemblies/indicesDatasets/f/163/proposals/188
    Related insights URL
    https://participate.indices-culture.eu/assemblies/hypotheses/f/170/posts/9
    Indicators
    Creator's revenues
    Evaluation
    "]
Eliminazioni
Aggiunte
  • +["<xml><dl class=\"decidim_awesome-custom_fields\" data-generator=\"decidim_awesome\" data-version=\"0.8.3\"><dt name=\"textarea-1635451235315\">Context</dt><dd id=\"textarea-1635451235315\" name=\"textarea\"><div>The live streaming platform Twitch underwent in recent years an impressive growth in terms of viewership and content diversity.The platform has been the object of several studies showcasing how streamers monetize their content via a peculiar system centered around para-sociality and community dynamics. Nonetheless, due to scarcity of data, lots is still unknown about the platform-wide relevance of this explanation as well as its effect on inequalities across streamers.</div></dd><dt name=\"text-1635451312580\">Hypothesis</dt><dd id=\"text-1635451312580\" name=\"text\"><div>Thanks to the recent availability of data showcasing the top 10,000 streamers revenue between 2019 and 2021, as well as viewership data from different sources, we characterized the popularity and audience monetization dynamics of the platform. Using methods from social physics and econometrics, we analyzed audience building and retention dynamics and linked them to observed inequalities. We found a high level of inequality across the platform, as well as an ability of top streamers to diversify their revenue sources, through audience renewal and diversification in monetization systems. Our results demonstrate that, even if the platform design and affordance favor monetization for smaller creators catering to specific niches, its non-algorithmic design still leaves room for classical choice biases allowing a few streamers to emerge, retain and renew a massive audience.</div></dd><dt name=\"text-1635451372562\">Collaboration</dt><dd id=\"text-1635451372562\" name=\"text\"><div></div></dd><dt name=\"text-1635451427513\">Related dataset URL</dt><dd id=\"text-1635451427513\" name=\"text\"><div>https://participate.indices-culture.eu/assemblies/indicesDatasets/f/163/proposals/188</div></dd><dt name=\"textarea-1669973821818-0\">Related insights URL</dt><dd id=\"textarea-1669973821818-0\" name=\"textarea\"><div>https://participate.indices-culture.eu/assemblies/hypotheses/f/170/posts/9</div></dd><dt name=\"textarea-1635451479530\">Indicators</dt><dd id=\"textarea-1635451479530\" name=\"textarea\"><div>Creator's revenues</div></dd><dt name=\"textarea-1635451518445\">Evaluation</dt><dd id=\"textarea-1635451518445\" name=\"textarea\"><div></div></dd></dl></xml>"]
Numero della versione 1 di 1 Mostra tutte le versioni Torna alla proposta
Autore della versione
Avatar: Riccardo Gallotti Riccardo Gallotti
Versione creata il 02/12/2022 12:29
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870792.
The sole responsibility for the content of this publication lies with the authors. It does not necessarily represent the opinion of the European Union.
Neither the EASME nor the European Commission is responsible for any use that may be made of the information contained therein.
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