Data Sources

Insight draws on the science of social media to design data collection sources and strategies, focusing on the core components of the sentiment ecosystem:

  • Information Sources: Ensuring coverage of mainstream sentiment sites in the cryptocurrency field

    • Social Media, including Twitter, TikTok, YouTube, etc.

    • News Media, including mainstream portals and news websites.

    • Forums and Discussion Groups, including Telegram, Discord, Reddit, etc.

    • Blogs and Personal Sites, including leading research and analysis sites.

    • Official Statements and Announcements.

  • Discussion Content: Focus on key elements that reflect crucial information in the discussion

    • Events and Topics: The core of sentiment discussions revolves around specific events or topics, such as news events, product releases, policy changes, etc.

    • Opinions and Views: Participants' opinions and attitudes toward events or topics, including supportive views and critical opinions.

    • Emotions and Sentiments: Emotions expressed in discussions, such as anger, joy, concern, fear, etc., significantly impact the direction and intensity of sentiment.

    • Facts and Data: Facts, data, evidence, and cases cited in discussions help support or refute opinions.

  • Participants: Ensuring comprehensive coverage of participants

    • General Public: Ordinary users are the primary participants in sentiment discussions, and their statements and interactions form the main body of sentiment.

    • Opinion Leaders: Influential individuals or groups, such as KOLs, whales, institutions, etc., whose views and actions often guide sentiment.

    • Stakeholders: Individuals or organizations directly related to events or topics, such as project parties, VCs, exchanges, etc., whose statements and actions also influence sentiment.

  • Distribution Channels: Content acquisition focused on differentiated nodes across distribution channels

    • Social Media Platforms: Monitoring how content spreads through sharing, reposting, commenting, etc., on social media platforms.

    • News Media: Tracking the dissemination and diffusion of news reports and comments.

    • Word of Mouth: Observing how sentiment information spreads among the public.

    • Automated Tools: Monitoring and separating the impact of recommendation algorithms on sentiment analysis objectivity, as bots and algorithmic recommendation systems play a significant role in sentiment dissemination, especially on social media platforms.