How to analyze sentiment in selected Reddit comments
Sentiment labels can help organize a discussion before a closer reading. On Reddit, the context of a reply often matters as much as the words in isolation.
Start with the right material.
- What you provide
- a small selection of readable Reddit comments with context.
- The intended result
- An evidence-linked analysis of selected comments.
How the workflow works.
Classify each supplied comment with its relevant parent context where available. Keep mixed, uncertain and sarcastic wording open to review rather than forcing every comment into a confident positive or negative label.
What to check in the result.
Inspect ambiguous examples and state the sample's boundaries. Comment frequency and sentiment describe the selected conversation, not the beliefs of an entire community or market.
Preview the Markdown to check headings, lists and links as well as the words. Keep source references with the document so a reviewer can trace important statements back to the material you supplied.
Learn from the worked example.
The downloadable Markdown example shows one possible organization of the result. Read it alongside the source example and notice which statements are recorded facts, proposed wording or questions still needing an answer.
The supplied example is illustrative. It is not a recorded run on your data.
Download the example ↓Use it with your own material.
- Open the source you want to work with and activate WebAct on that tab.
- Copy the task from the hero, add any required fields or preferences, and review the proposed actions.
- Compare the first result with your source. Ask for a specific correction or refinement where needed.