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Record W2595870896

FACEBOOK USERS’ HABITS IN GETTING COMMERCIAL INFORMATION: A STUDY ON HONG KONG STUDENTS

2016· article· en· W2595870896 on OpenAlexaboutno aff
Fanny Sau-Lan Cheung, Wing-Fai Leung

Bibliographic record

VenueEconomics Management and Financial Markets · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsnot available
Fundersnot available
KeywordsSocial mediaPromotion (chess)BusinessGuardianAdvertisingSocial media optimizationSocial media marketingMarketingPublic relationsDigital marketingPolitical science
DOInot available

Abstract

fetched live from OpenAlex

IntroductionSocial media, especially Facebook, MySpace and Twitter, have become very popular channels for companies to promote their brands or products. Many platforms, e.g. Social Media Week and Hong Kong Social Media Consortium, have been formed to provide opportunities for the companies to share their experience in making use of social media. Foreseeing the great business opportunities, firms were also established on focusing social media marketing. Actually, companies are willing to spend more on social media for promotion. For example, a study found that companies had increased 33.5% of advertising spend on social media 2015 compared with 2014 (eMarketer, 2015). When the firms are spending more marketing share on social media, surely they are concerned about the effectiveness of this new marketing tool. There are many studies on effectiveness from the perspectives of the firms' own evaluation. Many small companies, for example, found that the performance on building up branding and attracting new customers did not match the expectations (eMarketer.com, 2010).Social media are the trendy promotion channel for many companies. However, it is doubtful whether social media are so effective to reach the target customers. In fact, Facebook, the largest social network website, is currently losing users in the US, UK, Canada, Norway and Russia (The Guardian, 2011). It is not sure whether Facebook can keep users to stay for a long time. Moreover, due to the possible negative externalities of too many companies to promote through social media, it is not sure whether the effectiveness of social media is similar to e-mail advertising, which becomes less effective when the users simply neglect the messages when they get hordes of unknown messages.Understanding social media users' habits is very important for both marketers and academics. Marketers have to find out how to attract customers and maintain customer relationship through social media platforms. Academics are interested in understanding whether social media lead to different consumer behavior patterns and marketing strategies. This paper aims to seek for more information on social media users' usage purposes and preferences that will provide more insights to both practitioners and academics.In the paper, we plan to explore the Hong Kong young people's habits in using Facebook. We focus on Facebook as it is the largest social network website in the world and then it is the most representative. As internet penetration in Hong Kong is high (80.5% on 31 Dec. 2014, Internet World Stats, 2015) and there were 4.8 million Facebook subscribers in Hong Kong on 15 Nov. 2015 (Internet World Stats, 2015; the data were equivalent to 67.2% of the Hong Kong population if all accounts were owned by different people), behaviors of using Facebook in Hong Kong can be a reference for other areas. However, we do not only aim on the Facebook users, instead we want to have a broader view on the effectiveness of Facebook as a business channel. The respondents' purposes in using Facebook are investigated in order to explore whether Facebook is an effective business channel and then it should provide useful information to the companies whether they should put heavy investment on Facebook or not. Particularly, this study is a descriptive research that tries to describe the main characteristics of Facebook users' purposes of getting commercial information.Literature ReviewRecently there have been growing studies on social media. One line of the studies is the application of social media for WOMM. For example, Brown et al. (2007) found that online WOMM was not overwhelmingly favorable to the offline comments. Kozinets et al. (2010) studied in depth of 83 bloggers' comments and postings on a new camera-equipped mobile phone (MobiTech 3939) and classified the communication methods of the bloggers. Colliander and Dahlen (2011) compared the effectiveness of blogs and internet magazines by studying the feedbacks of readers on a same story of a brand of fashion. …

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.252
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations10
Published2016
Admission routes1
Has abstractyes

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