چكيده به لاتين
News has become an impartible part of our daily lives and news agencies, with news agencies publishing more than a thousand copies of news content every day. Not all these news articles are equally popular, so predicting popularity has become an important issue.Predicting the popularity of an article, a video, or any online content can properly control the marketing strategies and influence the marketing strategies. The popularity of news can be defined in a local or global setting. Local benchmarks are mainly used for use in a single news agency, while global scales help to identify the popularity of a news item in a news release from a variety of news agencies.Our research focuses on predicting popularity locally and predicting popularity of Tabnak news site based on feature analysis and selection of appropriate features from different news features such as views, number of comments, news release time, category, title length News, linking news to each other, news keywords using random forest algorithm. Several controversial news articles may be linked, causing a flood of comments. Therefore, the popularity was examined by considering the relationship between news articles. For this purpose, a 3-month autumn newsletter of 98 Tabanak sites was received by a reptile and implemented using a random forest model algorithm. Model test results and its evaluation indicate that the model performs well.
