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Record W1593160478

Impact of Internet Banner Advertisement on Social Media’S Consumer Buying Behaviour: A Case Study of Facebook

2015· article· en· W1593160478 on OpenAlexaboutno aff
Md.Anhar Sharif Mollah

Bibliographic record

VenueEuropean Journal of Business and Management · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicMarketing and Advertising Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsAdvertisingThe InternetSocial mediaQuarter (Canadian coin)BannerLoginBusinessProduct (mathematics)Computer scienceWorld Wide WebGeography
DOInot available

Abstract

fetched live from OpenAlex

Internet is the utmost imposing media of communication in this gen eternity. Internet users are increasing day to day. Every moment people are surfing internet for work purpose or passing their leisure time and connecting with the people. As a result they are connecting with the social media e.g. Twiter, Facebook and so on. People are chatting, sharing photo and connecting with the friends and family by the social media. Face book is really close to its admirers of the growth and the metrics of Facebook. It is really astounded that between the year of 2009 and 2000 the growth of international users. In the year of 2008, the total International Facebook users were 34 million people. The number had increased to 95 million by the first day of 2009 which had increased by 70% of the total Facebook users. Now the number of Facebook users is more than 400 million. Now a day the rate growing is increasing into the doubled digit in every month. In this quarter the rate of growth hastened by 25%. In 28 countries the rate is doubled in this quarter (Smith, 2010). The most important advantage of internet is the update information in all about the world. People are searching internet for update information and buy products because of most of the company using online as an advertising media to promote their product.In the modern era people are connected with friend and family using social media. Social media great place to advertisement because a person must be login into his or social media website. So the different organization taking this advantages and makes a new trend of advertisement. Online advertises comes into different forms like banner, pop up or pop down or in textual format. This internet advertises business is now blowing-out more than the traditional form advertising. There are two reasons behind the power of internet advertising media. That’s internet is the available almost each and every home and another one is the internet user is more than the summation of other media audience (Tavor, 2011). According to Berthon et al., (1996) article on internet advertising published in 1996 which was about the online classic banner advertisement. It creates interaction between consumer and the advertiser which was new era in the advertising world (Rappaport, 2007). An internet user usually browse different websites, blog, advertising, social medias and so on. Internet user may get their target information directly or when the search does not meet the target, then it can be moved to semi direct browsing. Occasionally internet custom browses without any specific target or a bit target which is known as undirected browsing (Brajnik and Gabrielli, 2010). Keywords: Facebook, Advertisement, User, Online, website etc.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.002
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.056
GPT teacher head0.274
Teacher spread0.218 · 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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Citations1
Published2015
Admission routes1
Has abstractyes

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