Teachers frequently use Twitter to engage in professional learning activities. A prominent example of teachers’ use of Twitter for such purposes is evident within the #NGSSchat community, which encouraged synchronous (at the same time) conversations between teachers and other educational stakeholders regarding the Next Generation Science Standards (NGSS) curriculum reform in the United States. Notably, #NGSSchat moderators archived the chats via the Storify platform, which has subsequently been used by researchers to understand science teachers’ professional learning activities on Twitter. However, what has not been established is the representativeness of this archive of #NGSSchat tweets. In other words, whether those who archived #NGSSchat content selected only a (potentially biased) selection of tweets is as yet unknown. Thus, in this study, we examined the Storify #NGSSchat database and compared it with raw data requests using the Twitter API. We found that the synchronous chats most data was adequately achieved. Contrarily (but as anticipated given what distinguishes the #NGSSchat community-synchronous conversations), the Storify #NGSSchat database did not capture most data outside these synchronous chat sessions. Importantly, we did not find an indication of systematic content- or user-driven tweet exclusion within the synchronous NGSS chat sessions on Storify, suggesting that the #NGSSchat archive via Storify (and potentially others like it) may be used by researchers for most research-related purposes.