What to prepare
- Permitted posts or conversation exports with source IDs and dates
- A research question, query terms and explicit collection boundaries
- A topic taxonomy with inclusion and exclusion rules
Research / RESOURCE DETAILS
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A research workflow for organizing permitted public or licensed conversation data into source-linked themes, questions and watch items. Define the collection boundary before interpreting the material: a selected channel or query is a view of a conversation, not a complete measure of public opinion. Keep examples and contrary cases attached to each theme so an operator can inspect the interpretation.
What you will produce
- A theme table with representative excerpts and source references
- A review queue for ambiguous sentiment, duplicates and emerging questions
- A dated listening brief separating observed material from interpretation
A closer look at the fit.
A working situation
A brand researcher reviews an authorized collection of public posts about a newly introduced feature. They build a topic register that distinguishes questions, complaints, comparisons, and unrelated uses of the brand name. The deliverable includes source links and collection limits, with a small ambiguity queue for human interpretation.
How should we treat reposts and repeated text?
Define whether the analysis concerns unique messages, unique sources, or distribution activity. Preserve those as separate measures where useful. Deduplicating everything can erase information about circulation; counting every copy as an independent opinion can inflate a theme. Document the chosen unit before interpreting frequency.
Can the output tell us what all customers think?
An observed collection supports claims about that collection, not automatically the whole customer population. State the platforms, search terms, dates, and inclusion rules. Use themes to identify research questions and examples for review, and avoid presenting an unrepresentative source set as a customer-wide vote.
PRODUCT NOTES & QUESTIONS / NORLA EDITORIAL
Understand the fit before you choose.
Editorial guidance about scope and evaluation. These notes are not buyer ratings or purchase reviews.
What to check
- Collection coverage, freshness and platform access depend on the approved sources; this description does not promise universal or real-time access.
- Automated sentiment labels can miss irony, language context and mixed opinions, and should not be treated as a population survey.
Can a theme count be described as the number of people who hold an opinion?
Only when the collection and deduplication support that interpretation. Otherwise label the unit as posts, comments or records. Several records may come from the same person, and the selected sources may exclude large parts of the intended audience.
How should ambiguous language be handled?
Preserve the original context and route the item for review instead of forcing a positive or negative label. A useful listening brief can include a mixed or unclear category and explain which examples require language or subject-matter expertise.
NORLA EDITORIAL / FIELD NOTES
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