The use of online social networking and quality of life

Tobi, Siti Noraini Mohd; Maon, Siti Noorsuriani; Ghazali, Norfazlina

doi:10.1109/time-e.2013.6611978

Cited by 7 publications

(4 citation statements)

References 7 publications

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“…Online Social Networks have continued to grow in number, quality, and significance, and with this, their influence on society is becoming more profound (Ahn et al 2007;Tobi, Ma'on, and Ghazali 2013;Mislove et al 2007). This is especially true due to the emergence of smartphones, wearables, and other smart mobile devices.…”

Section: Linkedin: a Trusted Professional And Business Mediamentioning

confidence: 99%

Data-Driven Deep Journalism to Discover Age Dynamics in Multi-Generational Labour Markets from LinkedIn Media

Alaql¹,

Alqurashi²,

Mehmood³

2022

Preprint

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We live in the information age and, ironically, meeting the core function of journalism – i.e., to provide people access to unbiased information – has never been more difficult. This paper explores deep journalism, our data-driven Artificial Intelligence (AI) based journalism approach to study how the LinkedIn media could be useful for journalism. Specifically, we apply our deep journalism approach to LinkedIn to automatically extract and analyse big data to provide the public with information about labour markets, people’s skills and education, and businesses and industries from multi-generational perspectives. The Great Resignation and Quiet Quitting phenomena coupled with rapidly changing generational attitudes are bringing unprecedented and uncertain changes to labour markets and our economies and societies, and hence the need for journalistic investigations into these topics is highly significant. We combine big data and machine learning to create a whole machine learning pipeline and a software tool for journalism that allows discovering parameters for age dynamics in labour markets using LinkedIn data. We collect a total of 57,000 posts from LinkedIn and use it to discover 15 parameters by Latent Dirichlet Allocation algorithm (LDA) and group them into five macro-parameters, namely Generations-Specific Issues, Skills & Qualifications, Employment Sectors, Consumer Industries, and Employment Issues. The journalism approach used in this paper can automatically discover and make objective, cross-sectional, and multi-perspective information available to all. It can bring rigour to journalism by making it easy to generate information using machine learning and can make tools and information available so that anyone can uncover information about matters of public importance. This work is novel since none of the earlier works have reported such an approach and tool and leveraged it to use LinkedIn media for journalism and to discover multigenerational perspectives (parameters) for age dynamics in labour markets. The approach could be extended with additional AI tools and other media.

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Section: Linkedin: a Trusted Professional And Business Mediamentioning

confidence: 99%

Data-Driven Deep Journalism to Discover Age Dynamics in Multi-Generational Labour Markets from LinkedIn Media

Alaql¹,

Alqurashi²,

Mehmood³

2022

Preprint

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“…Social connectedness, as a subjective perception of experience, is often measured with selfreported scales in quantitative studies. Researchers utilize many diverse operationalizations that are utilized to measure social connectedness on the level of individuals, including relationship salience [138], relationship satisfaction [53], feeling of closeness [138], loneliness [36], and quality of life [135]. The objective aspects of social connectedness are often measured on a macro level, primarily relevant to the network structure of a community [129].…”

Section: Measuring Social Connectedness During Remote Activitiesmentioning

confidence: 99%

Support Social Connectedness through Technology-mediated Shared Activities

Yuan

2021

Companion Publication of the 2021 Conference on Computer Supported Cooperative Work and Social Computing

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First and foremost, I would like to thank my advisor, Lana Yarosh. She has been a supportive and amazing mentor during my Ph.D. study. I feel lucky to have her as my advisor, whom I receive guidance and support from. I have received so much inspiration from all our conversations and interactions, which I cannot thank her enough for making me who I am as an HCI researcher. I would like to thank Professors Evan Suma Rosenberg, Loren Terveen, and ScottMcConnell for serving on my Ph.D. committee. Their valuable feedback and perspectives help me better shape and develop my research. I would also like to thank Professor Vipin Kumar for serving on the committee for my preliminary exams.Many thanks to my research collaborators for making all my research possible. To

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“…At the same time, another group of researchers found that social media activities have no influence on their behaviour. For example, Tobi et al (2013), Yunus et al (2013), and Deng and Tavares (2013) found their positive impact on students' health and academic performance, writing and vocabulary skills, and reflective ability and critical thinking skills. Conversely, Mitchell et al (2016), Jha et al (2016), Kowalski and Limber (2013) and Abaido (2019) argued that it has significant adverse outcomes on students' physical and mental health and academic performance.…”

Section: Introductionmentioning

confidence: 99%

Social Media Activities of Bangladeshi Secondary School Students and Its Influence on Students’ Behavior

Asaduzzaman

2023

AJC

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This study aimed to investigate Bangladeshi secondary school students' activities on their social media platforms and how those activities affect their behaviour. Applying the survey method with a mixed questionnaire among 400 secondary school students, this study explored both quantitative and qualitative data. Open and closed-ended questions both were used in the survey. In addition, a total of twenty students, eight parents, and eight teachers were also interviewed. This study found that students mainly use various social media platforms to fulfil their education, communication and entertainment needs. Their activities have more negative impacts on their behaviour than positive, which hampers their personal, social and educational lives. Moreover, it adversely affects their physical and mental health. In this context, parents and teachers are concerned and urged the government to set laws and policies prohibiting them from using it until a certain age.

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The use of online social networking and quality of life

Cited by 7 publications

References 7 publications

Data-Driven Deep Journalism to Discover Age Dynamics in Multi-Generational Labour Markets from LinkedIn Media

Data-Driven Deep Journalism to Discover Age Dynamics in Multi-Generational Labour Markets from LinkedIn Media

Support Social Connectedness through Technology-mediated Shared Activities

Social Media Activities of Bangladeshi Secondary School Students and Its Influence on Students’ Behavior

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