How Users' Personality Traits Predict Sentiment Tendencies of User-Generated Content in Social Media: A Mixed Method of Configuration Analysis and Machine Learning.

Objective: Social media content created by users with different personality traits presents various sentiment tendencies, easily leading to irrational public opinion. This study aims to explore the relationships between users' personality traits and sentiment tendencies of user-generated content (UGC).

Method: We crawled 18,686 tweets of 1, 215 users from Twitter to figure out the relationships between personality traits and sentiment tendencies.

1,5-Disubstituted tetrazoles as PD-1/PD-L1 antagonists.

The progress in cancer survival and treatment has witnessed a remarkable transformation through the innovative approach of targeting the inhibitory immune checkpoint protein PD-1/PD-L1 complex by mAbs, pembrolizumab (Keytruda). While generating 17.2 billion U.

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Mesothelioma of the tunica vaginalis testis (MTVT) is a rare tumour and a cause of hydrocele. This case report concerns a 26-year-old male with hydrocele treated with left hydrocelectomy. Histopathology revealed MTVT, and left radical orchiectomy was performed followed by chemotherapy.

Clock and riboswitch control of in tandem are essential for appropriate gauging of TDP levels under light/dark cycles in Arabidopsis.

Metabolic homeostasis is regulated by enzyme activities, but the importance of regulating their corresponding coenzyme levels is unexplored. The organic coenzyme thiamine diphosphate (TDP) is suggested to be supplied as needed and controlled by a riboswitch-sensing mechanism in plants through the circadian-regulated gene. Riboswitch disruption negatively impacts plant fitness.

Exploring users' content creation and information dissemination behavior in social media: The moderating effect of social presence.

Users' personality traits reveal different social media behavior characteristics. In order to explore the intrinsic relationships between personality traits and social media behavior, this study analyzes the influence of users' personality traits on social media content creation and information dissemination behavior, as well as the moderating effect of social presence. We collect users' personality data via questionnaires, crawl social media behavior data of samples from social media sites, and then establish regression models to test the research hypotheses.