Social Intelligence and Technology

Yang, Christopher C.; Yen, John; Liu, Jiming

doi:10.1109/mis.2014.28

Cited by 6 publications

(2 citation statements)

References 20 publications

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“…Blake, C suggested that while using social media and other technologies, there is a great need to improve the social intelligence of students [6]. Yang C, Yen J & Liu J established a study about how social intelligence can be used to solve various social problems arising due to the usage of social media [7].…”

Section: Introductionmentioning

confidence: 99%

Nomophobic Prevalence and Social Intelligence of Higher Secondary Students during COVID-19

Elias

Mirunalini

Paul³

2022

JPRI

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Aim: To identify the nomophobic prevalence and extent of social intelligence among adolescent students and identify the correlation between these variables. Study Design: Descriptive survey method. Place and Duration of Study: Various Higher Secondary schools in Kerala between June 2021 and December 2021. Methodology: 1068 higher secondary students were drawn for the study and the social intelligence and nomophobic prevalence of those students were identified using two standardised tools. The data collected wereanalysed to identify the level of their social intelligence and nomophobic prevalence, The correlation between these two factors was also studied. Results: The scores achieved by the sample were analysed appropriately and the quartile values on comparison show that the higher secondary students are having a moderate social intelligence and nomophobic prevalence. The correlation studies show that these factors are negatively correlated. Conclusion: Higher secondary students show moderate nomophobic prevalence, It should not be allowed to become an addiction. The negative correlation implicates that nomophobic prevalence decreases the social intelligence of adolescents.

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Section: Introductionmentioning

confidence: 99%

Nomophobic Prevalence and Social Intelligence of Higher Secondary Students during COVID-19

Elias

Mirunalini

Paul³

2022

JPRI

View full text Add to dashboard Cite

show abstract

“…Novel methods are being applied in areas such as homeland security, 1 crime prevention, 2 infrastructure management, cybersecurity, 3 intelligent transportation, healthcare and bioinformatics, 4,5 text mining, 6,7 fraud detection, 8 social media, 9 and decision support for complex tasks such as mergers and acquisitions. 10 In organizational settings, predictive analytics has gained widespread adoption over the past 10 years as fi rms look to "compete on analytics.…”

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confidence: 99%