Read the room.
Research the stock.
See what investors are saying, who is saying it, and how the conversation leans.
See what investors are saying, who is saying it, and how the conversation leans.
Where the author tagged their own post bullish or bearish on Stocktwits, that tag is used and the post is marked "Author tagged". Where there is no tag, the text is matched against simple bullish and bearish keyword lists and marked "Keyword estimate". Anything mixed, sarcastic or ambiguous stays unclassified. There is no language model and no sentiment score involved — each post shows which of the two methods produced its label, so a keyword guess is never presented as the author's stated position.
No, and the page says so beside the breakdown. What you are reading is a sample of recent public posts on one platform, not a poll of investors and not a survey of anybody who holds the stock. Popularity and bullishness establish neither accuracy nor direction. A small sample is flagged as small, because a handful of posts can swing the percentages entirely.
Posts come from a rolling recent window, the sample is capped at 100 posts, and results are cached for five minutes, so this is a current snapshot rather than a live feed or a history. The sidebar also counts distinct authors and posts from the last 24 hours, which is usually the more honest number: fifty posts from five accounts is a different thing from fifty posts from fifty.