Brands as personal narratives: learning from user–YouTube–brand interactions

Sashittal, Hemant C.; Jassawalla, Avan R.

doi:10.1057/s41262-021-00248-4

Cited by 6 publications

(4 citation statements)

References 110 publications

(113 reference statements)

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“…Third, a substantial portion of the literature already investigated the perspective of viewers (Gawer & Cusumano, 2014; Gal‐Or et al, 2018; McIntyre & Srinivasan, 2017), as well as advertisers (e.g., Hanna et al, 2011; Lee & Watkins, 2016; Sashittal & Jassawalla, 2022; Smith et al, 2012; Verhellen & De Pelsmacker, 2013). On the contrary, with the notable exception of Susarla et al (2012) and Bergvall‐Kåreborn and Howcroft (2014), the scant literature on content creators as complementors does not contribute to our understanding of how they exploit over time the digital platform.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Despite the growing interest in the scientific community, all these topics have been studied primarily from the perspective of the platform owner, also known as the ‘keystone firm’ (Cennamo et al, 2018), and what the platform owner should do in order to successfully manage its network and generate profits (Kim et al, 2017). Additionally, a relevant amount of extant research already examined advertisers' and viewers' perspectives (Gawer & Cusumano, 2014; Gal‐Or et al, 2018; McIntyre & Srinivasan, 2017; Smith et al, 2012; Sashittal & Jassawalla, 2022; Lee & Watkins, 2016; Verhellen & De Pelsmacker, 2013; Hanna et al, 2011). When these complementary actors are considered, the emphasis is on how they can increase their innovation capabilities through the platform ecosystem (Boudreau, 2010; Parker & van Alstyne, 2017; Wareham et al, 2014), how they act as a source of external knowledge (Eckhardt et al, 2018; Kapoor & Agarwal, 2017; Srinivasan & Venkatraman, 2018), and how they spur the platform's growth potential through complementary products or services (Anderson et al, 2014; Venkatraman, 2004).…”

Section: Introductionmentioning

confidence: 99%

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From mutualism to commensalism: Assessing the evolving relationship between complementors and digital platforms

Gastaldi,

Appio,

Trabucchi

et al. 2023

Information Systems Journal

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Digital platforms are increasingly dominating markets by bringing together two or more groups of users and facilitating the exchange of value between them. Although several significant issues concerning the dynamics of digital platforms have been addressed, much of the research effort has focused on the platform owner. On the other hand, research on complementors neither takes into account the individual level nor clearly shows what an individual complementor can do to benefit from platform participation. By studying the evolving relationship between YouTube and its ecosystem of complementors (content creators), we shed light on the strategies that complementors use to progressively avoid but still benefit from platform governance. We find that content creators are, first, in a mutual relationship with the YouTube platform, benefiting from direct monetization. Then, they shift to commensalism as the relationship evolves, allowing them to avoid YouTube's governance and take advantage of multi‐homing. Our findings illuminate the effects of platform governance, particularly how it shapes the actions of complementors.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

From mutualism to commensalism: Assessing the evolving relationship between complementors and digital platforms

Gastaldi,

Appio,

Trabucchi

et al. 2023

Information Systems Journal

View full text Add to dashboard Cite

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“…This has been associated with major societal impacts [2], triggering a debate on whether or not the personalization brings users on radicalization paths [3,4]. To a less extreme end, the problem of users getting a narrow view on the possibilities offered by the platforms has been studied qualitatively under the terms of filter bubbles [5][6][7], and more recently the rabbit-hole (shorthanded RH through the paper) phenomenon [4,[8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Modeling rabbit-holes on YouTube

Merrer

Trédan

Yesilkanat

2023

Soc. Netw. Anal. Min.

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Numerous discussions have advocated the presence of a so called rabbit-hole (RH) phenomenon on social media, interested in advanced personalization to their users. This phenomenon is loosely understood as a collapse of mainstream recommendations, in favor of ultra personalized ones that lock users into narrow and specialized feeds. Yet quantitative studies are often ignoring personalization, are of limited scale, and rely on manual tagging to track this collapse. This precludes a precise understanding of the phenomenon based on reproducible observations, and thus the continuous audits of platforms. In this paper, we first tackle the scale issue by proposing a user-sided bot-centric approach that enables large scale data collection, through autoplay walks on recommendations. We then propose a simple theory that explains the appearance of these RHs. While this theory is a simplifying viewpoint on a complex and planetwide phenomenon, it carries multiple advantages: it can be analytically modeled, and provides a general yet rigorous definition of RHs. We define them as an interplay between i) user interaction with personalization and ii) the attraction strength of certain video categories, which cause users to quickly step apart of mainstream recommendations made to fresh user profiles. We illustrate these concepts by highlighting some RHs found after collecting more than 16 million personalized recommendations on YouTube. A final validation step compares our automatically-identified RHs against manually-identified RHs from a previous research work. Together, those results pave the way for large scale and automated audits of the RH effect in recommendation systems.

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“…They have the capacity and capability to produce content on any topic or category. However, not all content posted on video platforms such as YouTube gets the desired attention, and only a fraction can reach a large audience, particularly the videos posted by social media marketers expecting millions of views [4][5][6][7][8]. Companies want to identify these categories with the highest potential for a high number of views on the platform, thereby maximizing profit while considering parameters affecting the quality and timeliness of video production and publishing.…”

Section: Introductionmentioning

confidence: 99%

AHP Approach for Determining Category in Social Media Content Creation in Order to Maximize Revenue per Mille (RPM)

Guzman

Robielos

2022

HighTech. Innov. J.

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This study utilizes the Analytic Hierarchy Process (AHP) in the selection of an optimal niche or category of videos for maximizing view count. The main income from videos is derived from RPM, which is a set amount per thousand views. A set of criteria was determined from attributes in the dataset that logically contribute to either the videos’ SEO or trend/popularity. The criteria in question were also determined by commonalities across a vast number of video content platforms, which focus more on the essential attributes of a video. In order to perform pairwise comparison, weights were derived from coefficients generated using Linear Regression. Following the creation of the model, we identify the categories with the highest potential for gaining views. Based on the results, the study may be performed in another time frame to reflect the major shifts in public interest over time. Thus, the importance of its repeatability and degree of usability across datasets from different platforms is emphasized. Doi: 10.28991/HIJ-2022-03-01-07 Full Text: PDF

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Brands as personal narratives: learning from user–YouTube–brand interactions

Cited by 6 publications

References 110 publications

From mutualism to commensalism: Assessing the evolving relationship between complementors and digital platforms

From mutualism to commensalism: Assessing the evolving relationship between complementors and digital platforms

Modeling rabbit-holes on YouTube

AHP Approach for Determining Category in Social Media Content Creation in Order to Maximize Revenue per Mille (RPM)

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