Subjects: Digital Publishing >> Internet Journals submitted time 2024-04-27
Abstract： Purposes : This paper analyzes the topic of highly read tweets in new media of laboratory medical journals, in order to reveal the hot spots and preferences of users, and guide the formulation of tweet topic optimization strategies, aiming at improving the communication power and influence of new media of laboratory medical journals. Methods : Taking the wechat public account of Laboratory Medicine (referred to as Laboratory Medicine ) as an example, Python programming was used to screen out the top 100 most-read tweets published on its platform from January 1, 2018 to May 31, 2023. Based on Latent dirichlet allocation (LDA) model, 100 tweets were identified and analyzed, and then the new media tweet topic optimization strategy was proposed. Findings : The topic of the highly read tweets of Laboratory Medicine are nucleic acid testing policy document for COVID-19 prevention and control , medical industry code of conduct , and vocational qualification examination and continuing education . Based on the topic identification and analysis, the topic optimization strategy of multi-voice polyphony (serial sub-topic development, new perspective topic deduction and case topic collection) is proposed. To stretch the narrative tension of the topic of tweets, from text to text, so as to enhance the depth and breadth of the topic of new media tweets in laboratory medical journals. Conclusions By identifying and analyzing the research topic of the highly read tweets of Laboratory medicine , it is helpful to formulate more accurate optimization strategies for the topic of tweets, and provides a basis for the research innovation and spatial expansion of the future topic of the highly read tweets of new media in laboratory medical journals.
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