theory-analysis-wom-motivation

To code cross-source evidence using Word-of-Mouth Motivation Theory, provide an analysis goal and evidence items with IDs, content, and content types. The skill calibrates interpretation logic and codes sharing motives across four subtheories.

You can analyze diverse qualitative data types for word-of-mouth motives, including interview summaries, customer service notes, social posts, research notes, and observations. The skill applies motive coding across these varied evidence sources.

To categorize sharing motives, the skill codes evidence into four dimensions: altruistic, social_identity, self_enhancement, and emotional_expression. It provides traceable quotes for each coded motive within these subtheories.

Yes, you can export theory annotations compatible with review-mining-stp for downstream STP workflows. The skill outputs a JSON and Markdown contract aligned with provided references to facilitate this integration.

No, this skill requires no external dependencies to function. It includes a complete theory portion and internal coding rules, calibrating the interpretation logic before analysis begins.