Modeling the function of advertising reviews from media ads on the YouTube channel

Блудова, Тетяна Володимирівна; Chuzhykov, Andrii; Leshchenko, Kateryna

doi:10.21511/im.15(3).2019.03

Cited by 6 publications

(6 citation statements)

References 16 publications

(4 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Item-Based Collaborative Filtering Algorithm. An itembased collaborative filtering algorithm does not use the content attributes of items to calculate the similarity between items but uses user behavior data to calculate the similarity between items [12,13]. It is proposed that there is a greater similarity between item A and item B, because most users who like item A also like item B [14,15].…”

Section: Journal Of Sensorsmentioning

confidence: 99%

[Retracted] Personalized Marketing Recommendation System of New Media Short Video Based on Deep Neural Network Data Fusion

Huang¹

2021

Journal of Sensors

View full text Add to dashboard Cite

With the rapid development of mobile Internet, short video has become another darling after traditional webcast in recent years. How to make full use of short video for effective marketing has become a hot issue that academia and industry are paying close attention to. This article is mainly aimed at exploring practical new media through in-depth research and exploration of the specific implementation methods and strategies of short video marketing in social media, based on the advantages and characteristic models of short video marketing in social media. The strategy of short video marketing in social media, and the use of highly in-depth neural network analysis technology for the personalized marketing recommendation system of new media short videos, so as to better promote the use of social media short videos by enterprises or individuals. We have to learn from marketing activities. The experimental results of this article show that when the data volume reaches 80%, the performance of the VRBCH algorithm steadily improves, so the performance of the main F of the VRBCH algorithm is still relatively ideal when the data volume changes. Due to the high dilution of the experimental data set, the amount of data in the VRBCH algorithm has increased sharply by 30% to 35%, but the purchase rate of the marketing recommendation system is as high as 98%. Therefore, the system has high feasibility.

show abstract

Section: Journal Of Sensorsmentioning

confidence: 99%

[Retracted] Personalized Marketing Recommendation System of New Media Short Video Based on Deep Neural Network Data Fusion

Huang¹

2021

Journal of Sensors

View full text Add to dashboard Cite

show abstract

“…Using the method of correlation-regression analysis, we find the parameters of the regression equation (Bludova et al, 2019). The constructed dependency function will look like:…”

Section: Figure 2 Empirical Regression Line Between Gross Regional Pr...mentioning

confidence: 99%

Innovative entrepreneurship policy in Ukraine and roadmap strategy

Zhadko¹,

Іlchenko²,

Holovnia

et al. 2022

Cuest. Pol.

View full text Add to dashboard Cite

Using an empirically based methodology, the scientific approaches to define the concepts of "innovation" and "innovation policy" are summarized. It is substantiated that the goal of implementing innovative entrepreneurship is the transition to an innovative model of development, which requires the implementation of the following priority tasks: integration of all stages of innovative entrepreneurship in the region; formation of competitive regional innovative products; increasing the level of quality of institutional infrastructure; improvement of information provision of innovative processes; stimulation of regional business entities to ensure innovative activity; creation of communications in the "science-production" system; ensuring quality training of specialists in the field of innovative entrepreneurship; development of knowledge-intensive industries; effective use of innovative potential and intellectual capital of the region. Modeling of the innovative entrepreneurship profile of the regions led to the conclusion that the main task, for each of the regions, is to develop measures to increase the level of formation of its innovative entrepreneurship space, which will have the effect of optimizing the economic results of the operation and increase its competitiveness in domestic and international markets.

show abstract

“…As with other marketing insights, logos, pathos, and ethos —logic, emotion, and credibility—can all be called upon in video strategies (Sohal and Kaur, 2019). “The use of display advertising enables companies to reach target audience and show them your ads on specific sites, which increases sales” (Bludova et al, 2019). The benefit of YouTube video ads is reaching a wide audience, and by sheer numbers, converting some to customers.…”

Section: Introductionmentioning

confidence: 99%

“…The benefit of YouTube video ads is reaching a wide audience, and by sheer numbers, converting some to customers. Various analyses for effectiveness focus on successive advertising clips, length of the clips, and the use of annotations for video clips (Bludova et al, 2019). Not just effective for consumer goods, Sohal and Kaur (2019) cite YouTube’s importance as a “bidirectional medium for political advertising and communication.”…”

Section: Introductionmentioning

confidence: 99%

Video advertising: Using YouTube analytics for the target audience

Manko

2022

Journal of Information Technology Teaching Cases

View full text Add to dashboard Cite

Video advertising takes many forms, from display ads, overlay ads, skippable and non-skippable videos, bumper ads, and sponsored cards, as well as the sponsored or branded content of the video itself on YouTube. With competition for user attention, the evolution of videos has turned advertisement into entertainment, and the analytics of how user interacts with videos and ads provides insight into consumer trends.

show abstract

Modeling the function of advertising reviews from media ads on the YouTube channel

Cited by 6 publications

References 16 publications

[Retracted] Personalized Marketing Recommendation System of New Media Short Video Based on Deep Neural Network Data Fusion

[Retracted] Personalized Marketing Recommendation System of New Media Short Video Based on Deep Neural Network Data Fusion

Innovative entrepreneurship policy in Ukraine and roadmap strategy

Video advertising: Using YouTube analytics for the target audience

Contact Info

Product

Resources

About