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Active in Structure: An Integrated M...
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Shao, Chun.
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Active in Structure: An Integrated Model of Structural Theories and Individual Factors in Explaining Audience Behavior in the Post-Network Age.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Active in Structure: An Integrated Model of Structural Theories and Individual Factors in Explaining Audience Behavior in the Post-Network Age./
Author:
Shao, Chun.
Published:
Ann Arbor : ProQuest Dissertations & Theses, : 2023,
Description:
218 p.
Notes:
Source: Dissertations Abstracts International, Volume: 85-02, Section: B.
Contained By:
Dissertations Abstracts International85-02B.
Subject:
Communication. -
Online resource:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30566887
ISBN:
9798380109475
Active in Structure: An Integrated Model of Structural Theories and Individual Factors in Explaining Audience Behavior in the Post-Network Age.
Shao, Chun.
Active in Structure: An Integrated Model of Structural Theories and Individual Factors in Explaining Audience Behavior in the Post-Network Age.
- Ann Arbor : ProQuest Dissertations & Theses, 2023 - 218 p.
Source: Dissertations Abstracts International, Volume: 85-02, Section: B.
Thesis (Ph.D.)--Arizona State University, 2023.
Over the past 60 years or so, audience researchers have strived to investigate the impact of structural and motivational factors on audiences' television viewing behaviors. With the popularity of streaming services, the way people consume and discuss media content has been fundamentally transformed. However, the academic understanding of whether factors traditionally found to impact television viewing behaviors continue to do so in the streaming age remains limited. Building on both agent-based and structural theories in television audience research, this study employed a mixed-method approach that combines data collected via in-depth interviews with that from screenshots captured with a browser extension to revisit the roles of structural and motivational factors in participants' Netflix viewing.The study's results underscore that, even in a high-choice media environment, structural factors (e.g., audience availability, content availability and exclusivity) and traditional viewing motivations (i.e. for relaxation and enjoyment) remain critical in determining participants' viewing practices. Specifically, the platforms and devices that people use to watch television may differ from those used in the network era, but why they watch, when they watch, and what they watch are still determined by the motivational and structural factors identified in traditional television audience research. In addition, the results showed that newer structural factors such as program scores on recommendation sites have less of an impact on participants' viewing decisions.Habits, which are commonly overlooked in audience research, played an important role in influencing when, how, and what participants watched on Netflix. Further, despite having access to almost unlimited viewing options, many participants still tended to watch programs that they were familiar with or had watched before. The findings highlighted that, even in today's fragmented media environment, participants' Netflix viewing practices were repetitive and deeply embedded in the structured routines of their daily lives. The study advances television audience scholarship by providing fresh insights about the traditional and emerging factors in determining viewers' streaming behaviors. Theoretical implications and future directions are discussed.
ISBN: 9798380109475Subjects--Topical Terms:
524709
Communication.
Subjects--Index Terms:
Audience behavior
Active in Structure: An Integrated Model of Structural Theories and Individual Factors in Explaining Audience Behavior in the Post-Network Age.
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Over the past 60 years or so, audience researchers have strived to investigate the impact of structural and motivational factors on audiences' television viewing behaviors. With the popularity of streaming services, the way people consume and discuss media content has been fundamentally transformed. However, the academic understanding of whether factors traditionally found to impact television viewing behaviors continue to do so in the streaming age remains limited. Building on both agent-based and structural theories in television audience research, this study employed a mixed-method approach that combines data collected via in-depth interviews with that from screenshots captured with a browser extension to revisit the roles of structural and motivational factors in participants' Netflix viewing.The study's results underscore that, even in a high-choice media environment, structural factors (e.g., audience availability, content availability and exclusivity) and traditional viewing motivations (i.e. for relaxation and enjoyment) remain critical in determining participants' viewing practices. Specifically, the platforms and devices that people use to watch television may differ from those used in the network era, but why they watch, when they watch, and what they watch are still determined by the motivational and structural factors identified in traditional television audience research. In addition, the results showed that newer structural factors such as program scores on recommendation sites have less of an impact on participants' viewing decisions.Habits, which are commonly overlooked in audience research, played an important role in influencing when, how, and what participants watched on Netflix. Further, despite having access to almost unlimited viewing options, many participants still tended to watch programs that they were familiar with or had watched before. The findings highlighted that, even in today's fragmented media environment, participants' Netflix viewing practices were repetitive and deeply embedded in the structured routines of their daily lives. The study advances television audience scholarship by providing fresh insights about the traditional and emerging factors in determining viewers' streaming behaviors. Theoretical implications and future directions are discussed.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30566887
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