Data Asset Value Evaluation of Internet Enterprises —— Take Sina Weibo as an Example

Empowering big data has become an important driving force to promote the digital transformation of enterprises and industrial transformation. However, there is no scientific and unified evaluation system for the accounting method of data assets. If the pricing standard of data assets is unreasonable, it will easily lead to chaos in the data market, which will lead to the loss of data assets. It can be seen that it is of positive significance to study the value of data assets and contribute to the benign development of data assets. On the one hand, this paper takes Sina Weibo, an Internet social media platform, as the research object, and comprehensively uses multi-period excess return model and B-S real option model to evaluate the value of data assets. In the data forecasting part, time series model is introduced to improve the smoothness of forecasting and reduce accidental fluctuations. On the other hand, through in-depth study of the annual report and other related materials, some data of enterprises are reasonably adjusted to reflect the actual situation and reduce the prediction error. Finally, the conclusion of the evaluation is summarized and analyzed, and the gains and shortcomings of the research are analyzed. At the same time, some problems and suggestions are given for the current risks and problems of the enterprise, hoping to help the development of the evaluation practice. 大数据赋能已成为推动企业数字化转型和产业变革的重要动力，然而，数据资产价值的核算方式对于目前来说并没有一个科学统一的评估体系，如果数据资产的定价标准不合理将容易造成数据市场混乱进而引起的数据资产价值亏损。可见，对数据资产价值进行研究是有积极的意义的，有助于数据资产的良性发展。一方面，本文以互联网社交媒体平台新浪微博为研究对象，综合运用多期超额收益模型和B-S实物期权模型进行数据资产价值评估，在数据预测部分，引入时间序列模型以提高预测的平滑性，减少偶然波动；另一方面，通过深入研究企业年报等相关资料，对企业的部分数据进行合理调整，使其能够反映实际情况，减少预测的误差。最后，对评估结论进行总结分析，分析研究的收获与不足，同时针对企业目前存在的风险和问题给出一些问题和建议，希望能够有助于评估实务发展。