Data accuracy is essential for reliable and valid altmetrics analysis. Although Twitter and Facebook altmetrics data are widely used for scholarly communication and scientific evaluation, few studies have tapped into their accuracy issue. Based on content analysis of random sample records over two phases, this study has investigated and compared the accuracy of Twitter and Facebook altmetrics data. Major conclusions are drawn as follows. (1) Three error types were identified from the altmetric data provider and six error types were identified from the altmetric data aggregator. Twitter and Facebook have shared most of the error types except for minor differences in the sub-categories. (2) The overall error rate is substantially high, being 17% and 32% for Twitter and Facebook respectively in April, 2019. However, except for publication date error and posting date error, the percentage of the other error types is relatively low (being around 3%). (3) The percentage of error types related to the dynamic nature of Twitter and Facebook is increasing over time, while percentage of error types concerning the bibliographic data is decreasing over time. (4) The error types are either “high seriousness low percentage” or “low seriousness high percentage”, therefore, they would probably not bring significant negative influence. (5) Underlying reasons of these error types are various. They could be attributable to the Twitter (or Facebook) user, Twitter (or Facebook) platform, altmetric database, as well as the third-party data provider. These results suggest that Twitter and Facebook altmetrics data in the Altmetric database are reliable on the whole, although there is still space for further improvement.

数据准确性对于可靠和有效的高度测量分析至关重要。尽管Twitter和Facebook测高数据已广泛用于学术交流和科学评估，但很少有研究涉及其准确性问题。基于两个阶段的随机样本记录的内容分析，本研究调查并比较了Twitter和Facebook测高数据的准确性。主要结论如下。（1）从测高数据提供者中识别出三种错误类型，并从测高数据聚合器中识别出六种错误类型。Twitter和Facebook共享了大多数错误类型，除了子类别中的细微差别。（2）总体错误率相当高，2019年4月Twitter和Facebook的总体错误率分别为17％和32％。但是，除了发布日期错误和发布日期错误外，其他错误类型的百分比相对较低（约为3％）。（3）与Twitter和Facebook的动态性质相关的错误类型的百分比随着时间的推移而增加，而与书目数据相关的错误类型的百分比则随着时间而减少。（4）错误类型为“高严重度低百分比”或“低严重度高百分比”，因此，它们可能不会带来重大的负面影响。（5）这些错误类型的根本原因是多种多样的。它们可能归因于Twitter（或Facebook）用户，Twitter（或Facebook）平台，测高数据库以及第三方数据提供者。这些结果表明，Altmetric数据库中的Twitter和Facebook altmetrics数据总体上是可靠的，