股价同步性刻画了股票波动与市场行业波动的同涨同跌现象。关于股价同步性的经济学含义主要有信息含量和噪音交易两种观点。随着经验证据的积累，学者发现股价同步性在不同制度环境、市场环境、信息环境可能有着不同含义，但由于特质信息和度量难度相对较大，相关研究以间接方法开展的居多。近年来，互联网技术改变了信息传播形态、方式和媒介。由于中国市场上散户投资者与网民身份高度重合，以微博微信为代表的即时通信、知乎为代表的知识分享、抖音快手为代表的短视频等社交媒体为散户投资者提供了无需调研便可全方位了解公司的渠道，其信息披露与传播作用在资本市场中的地位已不可忽视。相对于传统媒体以及各大财经网站论坛，社交媒体上仅能转发扩散公司重大财务和项目信息，但却能发布海量“非重大”与公司生产经营、项目进展、获奖评优、高管特征等信息，同时具备平等、及时、低成本特性，可精准推送和链式传播。这类公司相关的“非重大”信息是否会被大量无关信息所分散是一个值得探讨的课题。本文以2011—2020年中国A股主板上市并交易的公司作为研究样本，建立模型度量股价同步性，并通过爬虫技术确定上市公司及其管理层是否进行网络社交（及开通社交媒体账号并利用其发布信息），同时获取了每家账号进行网络社交的次数、发布内容、影响度等信息，用以研究上市公司社交媒体信息披露频次与内容与股价同步性的关系。本文还从部分指标替代变量、自我选择偏差、回归偏差、内生性等方面进行稳健性检验。实证结果表明：(1)开通网络社交账号的上市公司股价同步性更低，且网络社交程度越高，股价同步性越低。(2)网络社交发布的与公司基本面相关的信息比例与股价同步性的关系不显著；(3)信息不透明程度越高，上市公司网络社交对股价同步性降低作用越弱(更多发布无关信息)。(4)分析师关注度越高，上市公司网络社交对于股价同步性降低作用越强。即社交媒体信息通过分析师解读渠道进入股价。(5)上市公司网络社交强度越高，分析师盈余预测偏差越低。本文结论说明，上市公司在进行网络社交时能够披露反映公司基本面的特质信息，且这些信息经分析师的解读可被市场理解并进入股价提高信息效率。这表明上市公司在社交媒体上自愿披露的“非重大”信息对金融市场有意义。同时也为中国现阶段的A股市场股价同步性反映公司特质信息提供了经验证据。最后，本文的研究结论可对金融监管机构对社交媒体信息披露制定相应的规章制度提供实证证据。

The stock price synchronicity describes that the stock fluctuation and market industry fluctuation move up and down together. There are mainly two opinions on the meaning of economics on the stock price synchronicity, information content and noise deal. With the accumulation of empirical evidence, scholars find that the stock price synchronicity has different meanings in various mechanism environments, market environments and information environments. However, due to the trait information and bigger difficulty of measurement, most of the studies are carried out in the indirect form. In the past few years, Internet technology changes the communication form, method and media of information. Weibo, WeChat, Zhihu, Douyin and other social media provide channels for retail investors to comprehensively know about companies without doing research, so its information disclosure and communication role could not be ignored in the capital market. Social media releases vast of “non-important” information related to the production and operation of the company, award-winning and excellent appraisals, and characteristics of senior executives. Therefore, whether this “non-important” information related to a company would be scattered by vast of irrelevant information should be a topic worth discussing.The paper makes the companies listed and traded in the A-share main-board market in China from 2011 to 2020 as study samples to build up a model to measure the stock price synchronicity; besides, it confirms whether the listed companies and their executives would have social networking (and opening accounts of social media to release information with these) through the Python technology to study the relations between the frequency and contents of the social media information disclosure of listed companies and the stock price synchronicity. What’s more, the paper also makes the robustness analysis on the following indexes, including substitution variable, self-selection bias, error of regression and endogeneity. The empirical result shows that: (1) the social networking of the listed companies could reduce the stock price synchronicity; and the higher the degree of social networking, the lower the stock price synchronicity; (2) there is no significant relationship between the proportion of business information released by social network and the stock price synchronicity; (3) the higher information opacity, the weaker reduction of social networking of the listed companies on the stock price synchronicity (for releasing much more irrelevant information); (4) the higher attention from analysts, the stronger reduction of social networking of the listed companies on the stock price synchronicity, which means that social media information enters the stock price through analysts interpretation channels; (5) the stronger social networking of the listed companies, the lower deviation of analysts’ earnings forecast.The conclusion of the paper shows that the listed companies could disclose the trait information of the basic side of the companies through social networking, and this information would be understood by the market and enters into stock price through the interpretation of analysts to improve the efficiency of information. It implies that the listed companies voluntarily disclosing the “nonimportant” information on their social media are very meaningful for the financial market; meanwhile, it also provides empirical evidence for the stock price synchronicity in the current A-share market in China to show the trait information of the companies. In the end, the study conclusion of the paper would provide empirical evidence for prudential financial regulators to formulate correspondent laws and regulations on the information disclosure with social media.