计算机科学                        
                
                                
                        
                            控制(管理)                        
                
                                
                        
                            用户生成的内容                        
                
                                
                        
                            随机对照试验                        
                
                                
                        
                            内容(测量理论)                        
                
                                
                        
                            情报检索                        
                
                                
                        
                            万维网                        
                
                                
                        
                            社会化媒体                        
                
                                
                        
                            人工智能                        
                
                                
                        
                            医学                        
                
                                
                        
                            数学                        
                
                                
                        
                            数学分析                        
                
                                
                        
                            外科                        
                
                        
                    
            作者
            
                Neil Thompson,Xueyun Luo,Brian McKenzie,Edana Richardson,Brian Flanagan            
         
                    
        
    
            
            标识
            
                                    DOI:10.1287/isre.2023.0034
                                    
                                
                                 
         
        
                
            摘要
            
            User-generated content, for example, on Wikipedia, is easily accessed but has uncertain reliability. This makes it attractive to use but also creates risk, so there should be limits to who uses Wikipedia and for what purposes. In this paper, we use a randomized control trial to show that Wikipedia’s influence extends to judicial decision making, a field that is highly professional and supposed to follow strict procedures. This causal evidence further emphasizes the widespread influence of Wikipedia and other frequently accessed user-generated content on important social outcomes. Our findings also reveal boundaries to user-generated content’s influence. Although Wikipedia’s influence does extend to courts of “first instance” (where the case is first decided), it does not extend to higher courts (Court of Appeals, Supreme Court). These results suggest that normative prohibitions do seem to be sufficient to keep Wikipedia from influencing the most-important, well-resourced parts of law but that these prohibitions are insufficient in areas where time and resource pressures are greater. By showing that Wikipedia is influencing such an important and formal domain, our paper reinforces the importance of improving the accuracy and reliability of user-generated content, especially in domains with far-reaching societal consequences. Because there is no obvious way to prevent individuals from taking advantage of user-generated content professionally or nonprofessionally, our findings also contribute to the ongoing discussion of how to build public repositories of knowledge into more reliable storehouses.
         
            
 
                 
                
                    
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