User-interactive innovation knowledge acquisition model based on social media

Mainstream social media, such as Facebook, Twitter, and Weibo, provide enterprises an opportunity to innovate and develop. User-generated content on social media platforms can help determine the needs of the user and identify a target market, providing a basis for enterprise innovation. In this study, we propose a user-interactive innovation knowledge acquisition model. Accordingly, the comments data on a selected forum were first crawled using network crawler software. Subsequently, we pre-processed the data to obtain a semi-structured user corpus. We then used the Latent Dirichlet Allocation model to cluster topics and obtain the subject words that were hidden from each comment text. A user demand ontology was built based on the subject words, and with an expert's reference, the product function ontology was established. Through semantic similarity matching, we integrated two ontologies to obtain the user-interactive innovation knowledge acquisition model. Finally, the model was validated using the Volvo XC60 automobile as an example. The empirical results showed that the proposed model could assist enterprises by providing ideas for follow-up innovation and product development.