美媒对华报道态度因何而起？——以《纽约时报》为例

美国媒体对华报道中出现的倾向性态度一直是个值得关注的话题。基于媒体国际新闻报道态度模型，记者对报道态度的选择主要取决于社会对负面新闻的接受程度和新闻的重要程度。仅当社会对负面报道的接受程度较高时，媒体内部报道态度才会出现差异，即关联度较高的记者会倾向于负面报道，关联度较低的记者则倾向于正面报道。基于《纽约时报》对华新闻报道数据的实证研究结果显示，《纽约时报》记者比非《纽约时报》记者负面报道倾向性更高，新闻工作者相较自由记者更倾向于负面报道，这表明美国媒体对中国新闻的负面报道现象源于美国民众对中国新闻存在先验偏见。

What Drives U.S. Media Slanton China?—Take the New York Times as an Example

Chinese news reported by American media outlets is famous of its biased and tendentious reporting strategy, which could be understood as the portraying of China and its policies in a rather negative or critical perspective.As the increasing importance of public information, media slant on Chinese news has ever been applied to American political elections due to recent works. However, based on different research methods, scholars still did not come to an agreement on the existence of attitude deviation on Chinese news and its causes. As the rapid rise of innovative economic methods, the research about media slant on China could be done in a perspective of media economics. On the other hand, previous works pay more attention to biased reporting selections in domestic news reports. Most of the models are constructed under the condition of duopoly market where media outlets make their optimal choices with their political endorsement. This paper focuses on the characteristics of international news reports, which are barely examined by previous researches. Firstly, we construct a reporting-attitude model of international news, interpreting the internal mechanism of attitude deviation selection. We consider the international news market as a monopoly model, as media’s attitude strategies depend more on the ideology and values differences between two countries. Therefore, special impacts could be used to explain the reason of media deviation, such as journalists’ media relevance. The theoretical model reveals that the selections of journalists’ reporting strategies mainly depend on the degree of social acceptance of negative news and the importance of reporting news. Interestingly, only when the social acceptability of negative reports is high will there be a deviation between kinds of reporters, that is, journalists with higher relevance tend to report negatively, while journalists with lower relevance tend to report positively. Subsequently, based on the data of the New York Times’ news reports on China from 2010 to 2016, we build the Chinese news attitude index and test the accuracy of it with manual identification. Later, we use Probit model to prove the conclusion of the theoretical model. The results show that Times journalist tends to report more negatively than non-Times journalists, and journalists tend to report more negatively than freelance journalists. This is consistent with the conclusion of the theoretical model. Meantime, the difference of reporting attitude only appears in the field of international news with general news importance, which also verifies our theoretical analysis. These results not only accord with the analysis of the theoretical model, but also show that the negative Chinese news produced by American media originates from the priori prejudice of American public. Finally, after replacing the attitude index and controlling the missing variables, we find that the empirical results still support our conclusions. From the perspective of China, this paper provides a news framework of how to choose the reporting strategies when American media or other Western media report Chinese news. Through this framework, we observe the interaction effects between supply factors and demand factors whose impact on media deviation are mixed. Our work not only supplements the theories about impacts on media deviation and media bias, but also enriches the literature of U.S. media slant against China with new perspectives and methods. Furthermore, our work provides a new research method on designing media deviation or media bias index for more detailed conclusion proof. Previous work constructs indexes concerning media content without avoiding manual identification, which is easily questioned by indexes’ accuracy and artificial cognition problem. We think highly of the theoretical basis of the index and the accuracy proof from other ways, which make our index provable and exercisable with further research process.