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Article
Publication date: 23 March 2021

Ulya Bayram, Runia Roy, Aqil Assalil and Lamia BenHiba

The COVID-19 pandemic has sparked a remarkable volume of research literature, and scientists are increasingly in need of intelligent tools to cut through the noise and uncover…

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Abstract

Purpose

The COVID-19 pandemic has sparked a remarkable volume of research literature, and scientists are increasingly in need of intelligent tools to cut through the noise and uncover relevant research directions. As a response, the authors propose a novel framework. In this framework, the authors develop a novel weighted semantic graph model to compress the research studies efficiently. Also, the authors present two analyses on this graph to propose alternative ways to uncover additional aspects of COVID-19 research.

Design/methodology/approach

The authors construct the semantic graph using state-of-the-art natural language processing (NLP) techniques on COVID-19 publication texts (>100,000 texts). Next, the authors conduct an evolutionary analysis to capture the changes in COVID-19 research across time. Finally, the authors apply a link prediction study to detect novel COVID-19 research directions that are so far undiscovered.

Findings

Findings reveal the success of the semantic graph in capturing scientific knowledge and its evolution. Meanwhile, the prediction experiments provide 79% accuracy on returning intelligible links, showing the reliability of the methods for predicting novel connections that could help scientists discover potential new directions.

Originality/value

To the authors’ knowledge, this is the first study to propose a holistic framework that includes encoding the scientific knowledge in a semantic graph, demonstrates an evolutionary examination of past and ongoing research and offers scientists with tools to generate new hypotheses and research directions through predictive modeling and deep machine learning techniques.

Details

Online Information Review, vol. 45 no. 4
Type: Research Article
ISSN: 1468-4527

Keywords

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Article
Publication date: 24 April 2023

Deepika Bandil, Vivek Agrawal and R.P. Mohanty

Kids get exposed to advertising on social media platforms when they visit them to perform various goals. The purpose of this study is to find out the factors which affect kids'…

615

Abstract

Purpose

Kids get exposed to advertising on social media platforms when they visit them to perform various goals. The purpose of this study is to find out the factors which affect kids' behaviour when the kids encounter advertising on social media and also to establish causal relationships amongst the factors of social media advertising (SMA).

Design/methodology/approach

A total of 11 factors of SMA have been identified with the help of experts and the causal relationships amongst the SMA factors have been constructed by the implementation of decision-making trail and laboratory evaluation (DEMATEL). Based on the established relationships, a causal diagram has been also developed to understand the structural nature of interdependence amongst the factors.

Findings

DEMATEL technique is based on logical steps, which have assisted in categorising the identified factors into two groups: cause group and effect group. Cause group factors are the reasons for the effect group factors to occur. Customisation, entertainment, information and interactivity have been observed as cause factors whereas, relevance, engagement with SMA, purchase intention, product involvement, advertising value, attitude towards SMA and irritation have been observed as effect factors. Product involvement is found to have the highest level of interaction with all other factors. Information and interactivity are observed to influence all other factors.

Research limitations/implications

Kids possess a limited understanding of the selling intent of advertisers which makes kids vulnerable to advertising. This study supports that the content of the advertisement should be kept in accordance with the need of kids and also suggests that marketers should emphasise cause group factors which derive subsequent consequences on effect group factors. The foremost limitation of this study lies in the process of identifying the factors through expert opinions. The sets of contextual relationships may vary when different experts are considered.

Originality/value

This study strives to identify the factors which affect kids' understanding of SMA and also establishes causal relationships amongst them. This kind of study is unique in state of the art and to the authors' knowledge no significant research has been conducted in India which involves establishment of inter-relationships amongst SMA factors that affect kids' behaviour.

Details

Journal of Advances in Management Research, vol. 20 no. 3
Type: Research Article
ISSN: 0972-7981

Keywords

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