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1 – 10 of over 3000
Article
Publication date: 3 August 2020

Niyati Aggrawal, Anuja Arora, Adarsh Anand and Yogesh Dwivedi

The purpose of this study/paper is to propose a mathematical model that is able to predict the future popularity based on the view count of a particular YouTube video. Since the…

Abstract

Purpose

The purpose of this study/paper is to propose a mathematical model that is able to predict the future popularity based on the view count of a particular YouTube video. Since the emergence of video-sharing sites from early 2005, YouTube has been pioneering in its performance and holds the largest share of internet traffic. YouTube plays a significant role in popularizing information on social network. For all social media sites, viewership is an important and vital component to measure diffusion on a video-sharing site, which is defined in terms of the number of view counts. In the era of social media marketing, companies demand an efficient system that can predict the popularity of video in advance. Diffusion prediction of video can help marketing firms and brand companies to inflate traffic and help the firms in generating revenue.

Design/methodology/approach

In the present work, viewership is studied as an important diffusion-affecting parameter pertaining to YouTube videos. Primarily, a mathematical diffusion model is proposed to predict YouTube video diffusion based on the varying situations of viewership. The proposal segregates the total number of viewers into two classes – neoterics viewers, i.e. viewers those viewing a video on a direct basis, and followers, i.e. viewers those watching under the influence.

Findings

The approach is supplemented with numerical illustration done on the real YouTube data set. Results prove that the proposed approach contributes significantly to predict viewership of video. The proposed model brings predicted viewership and its classification highly close to the true value.

Originality/value

Thereby, a behavioral rationale for the modeling and quantification is offered in terms of the two varied and yet connected classes of viewers – “neoterics” and “followers.”

Article
Publication date: 22 June 2018

Claudia Margarita Acuña-Soto, Vicente Liern and Blanca Pérez-Gladish

In the last years, the use of free-online instructional videos has gained popularity among educators and students. Its success is mainly based on the provision of fast and…

Abstract

Purpose

In the last years, the use of free-online instructional videos has gained popularity among educators and students. Its success is mainly based on the provision of fast and inexpensive access to educational contents which can be consulted at the own convenience of students, all over the world. Free-online platforms as YouTube offer access to more than ten million instructional videos. The purpose of this paper is to assess and rank the educational quality of free-online instructional videos from a multidimensional perspective.

Design/methodology/approach

In this paper, the authors propose a MCDM approach based on a compromise ranking method, VIKOR. The approach integrates a normalization process which is especially suitable for situations where the nature of the different decision-making criteria is such that it does not allow homogeneous aggregation.

Findings

With the proposed normalization approach, the initial valuations of the alternatives with respect to the criteria are transformed in order to reflect their similarity with a given reference point (ideal solution). The normalized data are then integrated in a VIKOR-based framework in order to obtain those mathematical videos closer to the ideal video from the instructors’ perspective.

Originality/value

The ranking of instructional videos based on their quality from an educational multidimensional perspective is a good example of a real decision-making problem where the nature of the criteria, qualitative and quantitative, implies heterogeneous data. The proposed IS-VIKOR approach overcomes some of the problems inherent to this real decision-making problem.

Details

Management Decision, vol. 57 no. 2
Type: Research Article
ISSN: 0025-1747

Keywords

Book part
Publication date: 17 December 2003

Nanette Seago

For more than a decade there have been calls to change professional development and teacher education. A central task and challenge for teacher educators is to design learning…

Abstract

For more than a decade there have been calls to change professional development and teacher education. A central task and challenge for teacher educators is to design learning experiences that offer the greatest potential for improving teacher practice. Recently, videos of classrooms have emerged as tools for teacher learning. This chapter will consider the issues we faced attempting to create a coherent, sequenced professional development curriculum using video to help teachers improve mathematics teaching and learning. We will share some of the principles that guided the work, what we’ve been learning and indicate where we feel more research is needed.

Details

Using Video in Teacher Education
Type: Book
ISBN: 978-1-84950-232-0

Book part
Publication date: 2 February 2023

Robert C. Pennington, Monique Pinczynski and Kathryn Davis

Students with extensive supports needs (ESN) often require pervasive and intensive supports to access the full benefits of educational programming. In this chapter, the authors…

Abstract

Students with extensive supports needs (ESN) often require pervasive and intensive supports to access the full benefits of educational programming. In this chapter, the authors describe the application of both established and innovative technologies for promoting equitable access and opportunity for these students. They provide guidance for the use of technology across the areas of academic instruction, social communication, behavior supports, daily living, and employment.

Details

Using Technology to Enhance Special Education
Type: Book
ISBN: 978-1-80262-651-3

Keywords

Article
Publication date: 1 July 2005

G.Y. Hong, B. Fong and A.C.M. Fong

We describe an intelligent video categorization engine (IVCE) that uses the learning capability of artificial neural networks (ANNs) to classify suitably preprocessed video

Abstract

Purpose

We describe an intelligent video categorization engine (IVCE) that uses the learning capability of artificial neural networks (ANNs) to classify suitably preprocessed video segments into a predefined number of semantically meaningful events (categories).

Design/methodology/approach

We provide a survey of existing techniques that have been proposed, either directly or indirectly, towards achieving intelligent video categorization. We also compare the performance of two popular ANNs: Kohonen's self‐organizing map (SOM) and fuzzy adaptive resonance theory (Fuzzy ART). In particular, the ANNs are trained offline to form the necessary knowledge base prior to online categorization.

Findings

Experimental results show that accurate categorization can be achieved near instantaneously.

Research limitations

The main limitation of this research is the need for a finite set of predefined categories. Further research should focus on generalization of such techniques.

Originality/value

Machine understanding of video footage has tremendous potential for three reasons. First, it enables interactive broadcast of video. Second, it allows unequal error protection for different video shots/segments during transmission to make better use of limited channel resources. Third, it provides intuitive indexing and retrieval for video‐on‐demand applications.

Details

Kybernetes, vol. 34 no. 6
Type: Research Article
ISSN: 0368-492X

Keywords

Abstract

Details

Management Decision, vol. 57 no. 2
Type: Research Article
ISSN: 0025-1747

Content available
Article
Publication date: 1 August 2001

Gerry McKiernan

485

Abstract

Details

Library Hi Tech News, vol. 18 no. 8
Type: Research Article
ISSN: 0741-9058

Article
Publication date: 1 February 1991

Edward Valauskas

Creating a Bibliographic Workstation for Scientists and Engineers. A library workstation, in its simplest form, is a computer that provides access to bibliographic information…

1066

Abstract

Creating a Bibliographic Workstation for Scientists and Engineers. A library workstation, in its simplest form, is a computer that provides access to bibliographic information transparently in spite of its myriad forms. The conceptual kernel of this workstation is, more or less, a machine designed by, and for the use of, librarians and their staff, obstensibly to care and feed a bibliographic database. Suppose we expand our ideas on this particular kind of computer in order to invent a special species that will meet the demands of a critical clientele, for specialized literature.

Details

Library Workstation Report, vol. 8 no. 2
Type: Research Article
ISSN: 1041-7923

Article
Publication date: 2 March 2020

Liz Hassad de Andrade, Jorge Junio Moreira Antunes and Peter Wanke

The aim of this paper is to provide an approach to analyze the performance of TV programs and to identify what can be done to improve them.

Abstract

Purpose

The aim of this paper is to provide an approach to analyze the performance of TV programs and to identify what can be done to improve them.

Design/methodology/approach

The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the Ng-model, Grey relational analysis (GRA), and principal component analysis (PCA) were applied to evaluate the programs, using audience, share, and duration as the performance criteria.

Findings

By comparing TOPSIS to the Ng-model, PCA, and GRA, we verified that SVD and bootstrap SVD TOPSIS provide a good balance between equal-weights TOPSIS and the other models. This is because SVD and bootstrap SVD TOPSIS break down the data to a higher degree, but are less impacted by outliers compared to the long tail models.

Practical implications

To determine which TV programs should be replaced or modified is a complex decision that has not been addressed in the literature. The advantage of using a multi-criteria decision-making (MCDM) approach is that analysts can choose as many criteria as they want to rank TV programs, rather than relying on a single criterion (e.g., audience, share, target rating point).

Originality/value

This work represents the first time that robust MCDM methodology is applied to an audience data set to analyze the performance of TV programs and to identify what can be done to improve them. This study shows the application of a detailed methodology that is useful for the improvement of TV programs and other entertainment industry content.

Details

Benchmarking: An International Journal, vol. 27 no. 3
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 16 October 2009

Eunjin Kwon and Ki‐Joon Back

The main purpose of this paper is to overview and summarize all articles published in the UNLV Gaming Research & Review Journal (GRRJ) from 1994 to 2008, in order to understand…

804

Abstract

Purpose

The main purpose of this paper is to overview and summarize all articles published in the UNLV Gaming Research & Review Journal (GRRJ) from 1994 to 2008, in order to understand the gaming research trend.

Design/methodology/approach

A content analysis is performed on a total of 129 articles in 24 issues of GRRJ.

Findings

The paper suggests thematic content analysis and the trend of the research in order to better understand the scope of gaming research area.

Practical implications

The overview of GRRJ helps identify research gaps to suggest future research.

Originality/value

This paper is the first review of the GRRJ. It provides an overview of the research that is available to managers and researchers interested in the gaming business.

Details

Worldwide Hospitality and Tourism Themes, vol. 1 no. 4
Type: Research Article
ISSN: 1755-4217

Keywords

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