Research On The Influencing Factors Of The High Quality Authors' Willingness To Use Algorithmic Content Distribution Platforms

The development of the content industry is in the ascendant,content is flooding,but users still feel that there is few "good content",and the demand for personalized content is far from being met.The importance of high-quality content creators is beyond doubt.In the three mainstream content distribution platforms of editing,algorithm and social,the algorithmic content distribution platform can satisfy the user's personalized information acquisition requirements through data mining technology,and can also help content creators find more.Many readers.But the algorithm can't determine the quality,and the creators who absorb more high-quality content can make up for the lack of algorithm recommendation.This study focuses on those who have high-quality content creation capabilities,but have not tried or long-term stability in an algorithmic content distribution platform for content output.The title of "quality author" refers to "quality potential content creators",this article will Explore the key factors that influence these high-quality potential content creators to use an algorithmic content distribution platform.With regard to the definition of “quality content” and “quality author”,this paper mainly relies on the consensus formed in the industry and the various viewpoints of information quality evaluation in the academic circle.It is believed that the original content produced by a person in his professional field or in the field of expertise can be considered It is quality content,and people with high-quality content production capacity(or potential)are considered to be quality authors.This study collects data through questionnaires.Firstly,it combines interviews,small sample data exploratory factor analysis and reliability analysis to continuously correct and improve the questionnaire.At this stage,a comprehensive scale is obtained for follow-up research.Then,formal research is conducted to collect data.The validity and reliability of the scale are further verified by a confirmatory factor analysis method,and then the data is processed by the structural equation model analysis method,the model fit is tested,and the hypothesis proposed in the previous test is tested;finally,through the multi-group The structural equation model analysis method examines the cross-group effects of the three regulatory variables of age,gender,and major output content types.The study found that the impact of performance expectations on the willingness to use is not significant,and community influences and contributing factors have a significant impact on the willingness to use,with the most significant impact of community impact.It is understandable that enterprises pursue commercial interests,but at the same time,they must consider social responsibilities.Based on the research findings,this paper proposes suggestions for the practical operation of enterprises in platform operation,and achieves a balance between commercial profit-seeking and respect for creators to attract more high-quality content potential creators which could become loyal users of the platform.