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Displaying results 1 to 6 of 6.

  1. Work and value creation in the platform economy
    Author: Kenney, Martin; Zysman, John
    Published: September 9, 2018
    Publisher:  Berkeley, University of California, Berkeley Roundtable on the International Economy, [Berkeley, CA]

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: BRIE working paper ; 2018, 4
    Subjects: platform economy; user-generated content; venture labor; internet; work force; contractors
    Scope: 1 Online-Ressource (circa 49 Seiten), Illustrationen
    Notes:

    Forthcoming in Research in the Sociology of Work Kovalainen, A. and Vallas, S.(Eds.)
  2. Gender stereotypes in user-generated content
    Author: Kerkhof, Anna; Reich, Valentin Ferdinand Michael
    Published: July 2023
    Publisher:  CESifo, Munich, Germany

    Gender stereotypes pose an important hurdle on the way to gender equality. It is difficult to quantify the problem, though, as stereotypical beliefs are often subconscious or not openly expressed. User-generated content (UGC) opens up novel... more

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    Gender stereotypes pose an important hurdle on the way to gender equality. It is difficult to quantify the problem, though, as stereotypical beliefs are often subconscious or not openly expressed. User-generated content (UGC) opens up novel opportunities to overcome such challenges, as the anonymity of users may eliminate social pressures. This paper leverages over a million anonymous comments from a major German online discussion forum to study the prevalence and development of gender stereotypes over almost a decade. To that end, we develop an innovative and widely applicable text analysis procedure that overcomes conceptual challenges that arise whenever two variables in the training data are correlated, and changes in that correlation in the prediction sample are subject of examination themselves. Here, we apply the procedure to study the correlation between gender (i.e., does a comment discuss women or men) and gender stereotypical topics (e.g., work or family) in our comments, where we interpret a strong correlation as the presence of gender stereotypes. We find that men are indeed discussed relatively more often in the context of stereotypical male topics such as work and money, and that women are discussed relatively more often in the context of stereotypical female topics such as family, home, and physical appearance. While the prevalence of gender stereotypes related to stereotypical male topics diminishes over time, gender stereotypes related to female topics mostly persist.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/279329
    Series: CESifo working papers ; 10578 (2023)
    Subjects: gender bias; gender stereotypes; natural language processing; machine learning; user-generated content; word embeddings
    Scope: 1 Online-Ressource (circa 53 Seiten), Illustrationen
  3. The never ending book: the role of external stimuli and peer feedback in user-generated content production
    Author: Marchenko, Maria; Sonnabend, Hendrik
    Published: May 2022
    Publisher:  Vienna University of Economics and Business, Wien

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    VS 257
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Department of Economics working paper / Vienna University of Economics and Business ; no. 320
    Subjects: fanfiction; user-generated content; online public goods; voluntary contribution
    Scope: 1 Online-Ressource (circa 30 Seiten), Illustrationen
  4. Detecting coverage bias in user-generated content
    Author: Kerkhof, Anna; Münster, Johannes
    Published: January 2021
    Publisher:  CESifo, Center for Economic Studies & Ifo Institute, Munich, Germany

    The importance of user-generated content is growing as media consumption is moving online; yet, investigations of media bias on user-generated content platforms are rare. We develop a novel procedure to detect coverage bias – i.e., bias in the amount... more

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    The importance of user-generated content is growing as media consumption is moving online; yet, investigations of media bias on user-generated content platforms are rare. We develop a novel procedure to detect coverage bias – i.e., bias in the amount of coverage certain topics or issues receive – on user-generated content platforms. We proceed in two steps. First, we focus on a sample of homogeneous observations and control for observable differences. Second, we compare the coverage of our observations between different language versions of the same platform in a difference-in-differences framework, which allows us to disentangle coverage bias from unobserved heterogeneity between observations. We apply our procedure to Wikipedia and examine whether it has a coverage bias in its biographies of German (and French) Members of Parliament (MPs). Our analysis reveals a small to medium size coverage bias against MPs from the center-left parties in Germany and in France. A plausible explanation are partisan contributions to the Wikipedia biographies, as we show by analyzing patterns of authorship and Wikipedia’s talk pages for the German case. Practical implications of our results include raising users’ awareness of coverage bias when searching for and processing information obtained on user-generated content platforms.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/232441
    Series: CESifo working paper ; no. 8844 (2021)
    Subjects: coverage bias; media bias; media economics; social media; user-generated content
    Scope: 1 Online-Ressource (circa 48 Seiten), Illustrationen
  5. Detecting coverage bias in user-generated content
    Author: Kerkhof, Anna; Münster, Johannes
    Published: [2021]
    Publisher:  ECONtribute, Bonn

    The importance of user-generated content is growing as media consumption is moving online; yet, investigations of media bias on user-generated content platforms are rare. We develop a novel procedure to detect coverage bias - i.e., bias in the amount... more

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    DS 711
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    The importance of user-generated content is growing as media consumption is moving online; yet, investigations of media bias on user-generated content platforms are rare. We develop a novel procedure to detect coverage bias - i.e., bias in the amount of coverage certain topics or issues receive - on user-generated content platforms. We proceed in two steps. First, we focus on a sample of homogeneous observations and control for observable differences. Second, we compare the coverage of our observations between different language versions of the same platform in a difference-in-differences framework, which allows us to disentangle coverage bias from unobserved heterogeneity between observations. We apply our procedure to Wikipedia and examine whether it has a coverage bias in its biographies of German (and French) Members of Parliament (MPs). Our analysis reveals a small to medium size coverage bias against MPs from the center-left parties in Germany and in France. A plausible explanation are partisan contributions to the Wikipedia biographies, as we show by analyzing patterns of authorship and Wikipedia's talk pages for the German case. Practical implications of our results include raising users' awareness of coverage bias when searching for and processing information obtained on user-generated content platforms.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/228860
    Series: ECONtribute discussion paper ; no. 057 (January 2021)
    Subjects: bias; media bias; media economics; social media; user-generated content
    Scope: 1 Online-Ressource (circa 47 Seiten), Illustrationen
  6. The economics of social media
    Author: Aridor, Guy; Jiménez Durán, Rafael; Levy, Ro'ee; Song, Lena
    Published: January 2024
    Publisher:  CESifo, Munich, Germany

    We review the burgeoning literature on the economics of social media, which has become ubiquitous in the modern economy and fundamentally changed how people interact. We first define social media platforms and isolate the features that distinguish... more

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    We review the burgeoning literature on the economics of social media, which has become ubiquitous in the modern economy and fundamentally changed how people interact. We first define social media platforms and isolate the features that distinguish them from traditional media and other digital platforms. We then synthesize the main lessons from the empirical economics literature and organize them around the three stages of the life cycle of user-generated content: (1) production, (2) distribution, and (3) consumption. Under production, we discuss how incentives affect content produced on and off social media and how harmful content is moderated. Under distribution, we discuss the social network structure, algorithms, and targeted advertisements. Under consumption, we discuss how social media affects individuals who consume its content and society at large, and discuss consumer substitution patterns across platforms. Throughout the review, we delve into case studies examining the deterrence of misinformation, segregation, political advertisements, and the effects of social media on political outcomes. We conclude with a brief discussion on the future of social media.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/296023
    Series: CESifo working papers ; 10934 (2024)
    Subjects: social media; media economics; user-generated content
    Scope: 1 Online-Ressource (circa 51 Seiten), Illustrationen