Abstract: Product users publish ideas on the open innovation platform established by the enterprise. The degree of recognition indicates whether the idea is welcomed or not, which is an important indicator to measure the quality of the idea. Through the signals conveyed by creative texts, valuable ideas can be quickly and efficiently identified. Based on the signal theory,we propose five language signals from the aspects of information and emotion, and build a theoretical model of the influence of language signals on idea recognition by 10818 ideas on Salesforce TrailBlazer Community. The results show that information uniqueness, text readability, and emotional valence signals have a positive impact on idea recognition, and subject diversity and emotional subjectivity have a negative impact on idea recognition. The conclusions of this research help open innovation platform managers to deepen their understanding of the characteristics of creative texts and formulate more complete operational strategies.

Key words: Open innovation platform, Text characteristics, Signal theory, Idea recognition, Creative text, Product innovation