Making Decisions about Self-Disclosure in Online Social Networks

Heravi, Alireza; Mani, Deepa; Choo, Kim‐Kwang Raymond; Mubarak, Sameera

doi:10.24251/hicss.2017.233

Cited by 7 publications

(5 citation statements)

References 32 publications

(44 reference statements)

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“…According to Pew Research Center research ( Rainie et al, 2013 ), 28% of Facebook users said the site has become less important to them. Other scholars showed a similar finding that one of the major risks of using social media is it wastes people’s time ( Heravi et al, 2017 ).…”

Section: Introductionmentioning

confidence: 67%

Why People Don’t Use Facebook Anymore? An Investigation Into the Relationship Between the Big Five Personality Traits and the Motivation to Leave Facebook

Hong

2020

Front. Psychol.

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This study linked the big five personality traits with motivational factors to leave Facebook based on a survey of 218 former Facebook users. The big five were related with eight main factors retrieved from existing literature. Results showed that neuroticism was positively related to addiction, banality, peer pressure, and privacy while conscientiousness was negatively related to peer pressure, addiction, annoyance, and emergence of new platforms. Openness was positively related with banality but negatively with addiction and peer pressure. Theoretical and practical interpretations are also discussed.

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Section: Introductionmentioning

confidence: 67%

Why People Don’t Use Facebook Anymore? An Investigation Into the Relationship Between the Big Five Personality Traits and the Motivation to Leave Facebook

Hong

2020

Front. Psychol.

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“…According to Fig. 10, the social hot-spot of pedestrians is around (15,13) while the hot-spots of Pokémon GO players 390 are located in grid (13,15) and (15,8), where have most of pokémons gathered.…”

Section: Change On Social Network and Social Behaviourmentioning

confidence: 99%

“…were also studied. For example, Heravi et al studied the privacy calculus decision making processes in OSN[15], and David et al found that a static network is more helpful in constructing stronger cooperation than traditional population distribution[16]. Apart from the single social network, there are also few studies about the symbiotic social network.…”

mentioning

confidence: 99%

Pokémon GO in Melbourne CBD: A case study of the cyber-physical symbiotic social networks

Wang¹,

Wu²,

Wen³

et al. 2018

Journal of Computational Science

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“…The number of live streaming platforms and the audiences are both remarkably increasing [1,2] recently. For example, Douyu, the biggest live streaming platform in China, announced that the number of active users per month reached to 1.5 billion.…”

Section: Introductionmentioning

confidence: 99%

RIMS: A Real-time and Intelligent Monitoring System for live-broadcasting platforms

Ren

Zhu

et al. 2018

Future Generation Computer Systems

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Personal live shows on Internet streaming platform currently is blooming as a popular application and attracting several millions of users. The content supervision of live streaming platform, in which hundreds of show rooms perform synchronously, is a major concern with the development of this new kind of service. Traditional image captures and real-time content analysis experience huge difficulties, such as processing delay, data overwhelming and analysis overhead. In this paper, we propose several novel methods and algorithms to monitor real-time live stream and identify illegal live misbehavior intelligently based on state of perception and frame difference analysis. The proposed system makes use of several indicators of the chatting room status rather than analyzing images solely and directly. Three kinds of detecting techniques are adopted: self-adaptive threshold-based abnormal traffic detection, sensitive comments perception, and state evaluation. The proposed system captures the segmentation of video scenes by frame difference analysis, and pays more attention on the showing room that has large scene changes. We deploy our system to monitor a typical live platform called panda.tv, and the overall accuracy of three indicators reaches 90.1%. The application of this system can change current situation where the live platform supervision totally depends on manual review. The key techniques in this system can be widely employed in many applications, such as live broadcast platform industries, video surveillance for state security, and the national security for counter-terrorism.

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Making Decisions about Self-Disclosure in Online Social Networks

Abstract: This paper explores privacy calculus decision making processes for online social networks (OSN

Cited by 7 publications

References 32 publications

Why People Don’t Use Facebook Anymore? An Investigation Into the Relationship Between the Big Five Personality Traits and the Motivation to Leave Facebook

Why People Don’t Use Facebook Anymore? An Investigation Into the Relationship Between the Big Five Personality Traits and the Motivation to Leave Facebook

Pokémon GO in Melbourne CBD: A case study of the cyber-physical symbiotic social networks

RIMS: A Real-time and Intelligent Monitoring System for live-broadcasting platforms

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