Why Users are Information Monophagism in the Era of Algorithms:Generation Process,Driving Factors and Correction Strategies
The article takes the public corpus of information monophagism on the Internet as the data source,and uses inductive content analysis and MAXQDA qualitative analysis software to conduct coding analysis,identifying a total of 848 codes,which are categorized into five major components:drivers,group distribution,type distribution,impact results and correction strategies,and in this way,constructing and elaborating on the logic of the process of generating information monophagism.The study found that information monophagism can be classified into four types:active,passive,social and anxiety,and is affected by both subjective factors(self-identity,cognitive bias,psychological state and selective exposure)and objective factors(algorithmic manipulation,solidification of information paths,and double hostage of information capital);it has the positive effects of promoting countercocooning,professional refinement,and technological embodied reflection.However,the negative impact is even greater,and it is easy to cause problems such as information silos,imbalanced information structure,solidified thinking,homogeneous information fatigue,group polarization,and empathetic deviation.Based on this,we put forward the correction strategies of subject self-awareness-cultivating users'diversified literacy,platform self-control-establishing reverse recommendation engineering,and legal regulation-guiding technical algorithms to be good.
Information monophagismInductive content analysisGeneration processDriving factorCorrection strategy
NETL
NSTL
万方数据
