Abstract
The evaluation of the value of news communication is an area that deserves more attention, but there has been a dearth of specific research in this area. We must first determine the positioning of the news dissemination activity in order to study the mechanism for evaluating the effect of news dissemination. Fundamentally, assessing the impact of news dissemination is a dialectical balance of accuracy and effectiveness. I can conduct research from the three dimensions of policy orientation, communication orientation, and audience orientation and scientifically evaluate the effect of news communication on a qualitative and quantitative basis, based on the main body of the publisher. With only a small amount of labelled data, a high-quality news propagation value evaluation can be achieved. The value is rationally searched in the era of algorithm recommendation. The traditional “personalised recommendation algorithm” caters to the audience’s interests in one direction, with the goal of gaining their attention and commercial success. The “personalised recommendation algorithm” primarily uses statistical methods in the processing of news information, such as user’s basic information and behaviour information, and does not investigate the attributes and functions of news facts or the quality of news information itself. The research proposed in this paper suggests attempting to design an algorithm based on “news value.” First, it is based on the premise of a rational and caring “public person” who is concerned about the public interest, as well as professional journalistic news selection criteria. “News value” is a theoretical foundation for algorithm design that considers not only the publicity of news but also the audience’s interests. More importantly, this type of algorithm is designed to judge the quality and value of information based on how well the information is understood and then make a decision, returning to the essence of news facts and information.
Highlights
Academic Editor: Xin Ning e evaluation of the value of news communication is an area that deserves more attention, but there has been a dearth of specific research in this area
With only a small amount of labelled data, a high-quality news propagation value evaluation can be achieved. e value is rationally searched in the era of algorithm recommendation. e traditional “personalised recommendation algorithm” caters to the audience’s interests in one direction, with the goal of gaining their attention and commercial success. e “personalised recommendation algorithm” primarily uses statistical methods in the processing of news information, such as user’s basic information and behaviour information, and does not investigate the attributes and functions of news facts or the quality of news information itself. e research proposed in this paper suggests attempting to design an algorithm based on “news value.”
The news release activity itself is a communication activity, and it is suitable for the attention of the communication effect research mechanism [2]. erefore, in many communication effect research works, the effect evaluation of political communication activities will involve the effect of news release [3]
Summary
New Media Communication Department, School of Humanities, Jiamusi University, Jiamusi 154002, China. Is paper aims to build a communication effect evaluation system for news communication value evaluation using the deep neural network algorithm. E current news value evaluation method designed by scholars has a high degree of deep dependence and can process a small amount of data. Erefore, this paper proposes a standard for judging news value and introduces a deep neural network model, hoping to realize the automatic evaluation and batch calculation of news value. If something can affect the vital interests of the broadest masses of the people, it must be very important It mainly includes the following aspects: the number of people affected by the facts, the size of people’s interests, the length of time of influence, and the breadth of the influence space.
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