Performance evaluation of Persian News Agency on the Twitter using a combination of Data mining, analytical network analysis (ANP) and data envelopment analysis (DEA)

The irreplaceable role of social networks in human life is undeniable and many people nowadays follow the news through social networks. That's why news media have expanded their coverage through social networks such as Twitter. Evaluating the performance of news agencies on social networks can help them to improve their performance and ultimately attract the audience. In fact, evaluating news techniques to attract the audience and guide public opinion in the desired direction of the media is one of the most important aims of media policy makers. To this end, it seems necessary to provide new and efficient methods for quantitative and qualitative evaluation of the performance of news media. In this research, a three-step method is proposed. In the first stage, the criteria and sub-criteria were ranked using network analysis method. The results of these two steps are used in the data envelopment analysis method and efficient media are identified. The efficient media are then ranked using the Andson-Peterson method. This method was tested on 15 Persian- news networks on Twitter, and the most popular Persian media were ranked. The results indicated that the model used is a suitable and efficient model for evaluating and ranking Persian news networks. Al-Arabiya Farsi, Deutsche Welle Farsi and The Indypersian were selected as the most efficient medias, respectively. The results obtained in comparison by similar researches and the opinion of experts indicated that the proposed model is a suitable and efficient model for evaluating and ranking Persian news agencies