Researchers discovered people with a specific variant of the oxytocin receptor gene OXTR follow more people on Instagram. However, there no evidence was found to suggest gene-environment interactions influence online sociability.
The prevailing theory is removing toxic social media users from accessing their accounts will prevent them from posting harmful content. Researchers say banned users increase their toxic postings via more lenient platforms when removed from top networks.
Social media influencers take note, posting images of fatty foods increases follower engagement, researchers report.
A newly developed artificial intelligence algorithm can accurately detect sarcasm in comments written on social media platforms.
Sharing our personal experiences on social media may negatively impact how we feel about our memories, especially if the post doesn't get many likes, a new study reports.
Study reveals a link between social media addiction and cyberbullying in teens. Researchers found those who spent more hours online checking social media sites were more likely to display cyberbullying behaviors. This was especially true for males.
The use of social media, specifically to drive "likes" to our content, follows a pattern of "reward learning", much like when an animal is trained to seek food rewards.
Young adults who spend 300 or more minutes on social media a day are 2.8 times more likely to develop depression within six months than those who use social media for 120 minutes or less.
Personality traits, such as empathy and extraversion, could be predicted from specific network features. Other personality traits, lifestyle, and mental health status can be predicted from language use on social media platforms.
With so much of our lives shared online, researchers question what will happen to our social media information after we die.
Linguistic analytic models found users who tweet about loneliness post significantly more frequently about mental health concerns, relationship problems, and insomnia.
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A new deep learning system is 90% accurate in identifying cyberbullies on the popular social media site Twitter.
