2018
DOI: 10.20547/jms.2014.1805203
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Customer Attitude towards Online Ads of Smartphone Brands: A Netnographic Analysis of User Generated Comments on YouTube

Abstract: Today ads are no more one-sided communication but a mixture of online and offline channels developed for the sake of direct interaction with the communities. YouTube in specific and other online video platforms in general have shifted paradigm of TV commercials altogether for many brands.Just like other product brands, smartphone brands have also their presence on social media including YouTube and have their channels at it. The smartphone online ads on YouTube gain millions of views, thousands of likes, and d… Show more

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Cited by 4 publications
(6 citation statements)
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“…While research has explored user responses to advertisements in terms of attitudes toward the brand and the ad itself (MacInnis and Jaworski, 1989), the focus of YouTube advertising research has mainly been on quantitative metrics such as likes, dislikes and view counts (Rashid and Zeeshan, 2018). This emphasis on quantitative analysis leaves a gap in the literature regarding the qualitative content analysis of YouTube comments and their replies, which could provide valuable insights into user attitudes (Feng et al , 2019).…”
Section: Youtube Comments and User Responsementioning
confidence: 99%
“…While research has explored user responses to advertisements in terms of attitudes toward the brand and the ad itself (MacInnis and Jaworski, 1989), the focus of YouTube advertising research has mainly been on quantitative metrics such as likes, dislikes and view counts (Rashid and Zeeshan, 2018). This emphasis on quantitative analysis leaves a gap in the literature regarding the qualitative content analysis of YouTube comments and their replies, which could provide valuable insights into user attitudes (Feng et al , 2019).…”
Section: Youtube Comments and User Responsementioning
confidence: 99%
“…This moves the traditional perspective of the customer as a passive receiver of value to an active creator of value during value co-creation (Pera et al, 2016). Hence, brand equity is now considered to be rooted in the interaction between producer and buyer (Rashid & Zeeshan, 2018).…”
Section: Literature Reviewmentioning
confidence: 99%
“…For example, text mining techniques have come a long way from being used only for books, patents, and scholarly articles to nowadays covering social media and other online content, as well as brand-related online sentiment [21][22][23][24][25]. Modern social media research builds on web scraping tools like Facepager and Netvizz [26] as well as a variety of text processing techniques, software packages, and algorithms (with statistically demanding calculations based on latent Dirichlet allocation (LDA) [24,27,28] to text mining packages for automated text mining, such as "NVivo", "QDA Miner", the "qdap" package in R and "AntCont" [23,26,29,30]). Keyword extraction algorithms, e.g., PositionRank, TextRank, and RAKE, thereby rely on predefined dictionaries of keywords (rapid automatic keyword extraction) [31,32].…”
Section: Introductionmentioning
confidence: 99%