| With the continuous development of the game industry,domestic personal computer(PC)games have developed to a new stage,which forces domestic game companies to meet players’ demands more timely and accurately.At the same time,with the advancing of science and technology brought by the era of big data,text mining technology has been applied in many fields.However,few studies on online review analysis focus on PC game.Therefore,this study crawls 70435 valid online reviews of domestic PC games on Steam platform,and then tries to find out the concerns and demands of Chinese players towards domestic PC games by aspect extraction and sentiment mining of review texts.The main results are as follows.For aspect mining,Chinese players pay more attention to the story,game type,gameplay and gaming mechanism,props and skill of game,character and multiplayer mode in the game.The word "hope" appears most frequently,which reflects the most intense sentiment expression of Chinese players towards domestic PC games for recognition,expectation,urge and acceptance of the current imperfect gaming quality.For sentiment analysis,we also find out that the overall sentiment tendency of Chinese players towards domestic PC games is positive,but the sentiment score is not high.More of them show slight sentiment tendency,and less middle and heavy sentiment tendency are represented.The sentiment feedback of Chinese players towards domestic PC games is not strong,indicating that the quality of domestic PC games is not good.On the whole,Chinese players have high expectations on domestic PC games,but their evaluation towards the quality of current games is not high.Domestic game companies also need to constantly optimize and form their own advantages in six aspects,including responding to player demands timely,improving the level of story creation,balancing the game and innovating the gameplay,shaping three-dimensional character image,and developing multiplayer online mode. |
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