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Toolbox for the Structural Analysis of Narratives: The Scatter Plot of Entities and the Narrative Flow Graph

Narrative Analysis

ID: 2021-054 Toolbox for the Structural Analysis of Narratives: The Scatter Plot of Entities and the Narrative Flow Graph

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Invention Market Information
Commercialization and Marketing Report
Entrepreneur Plan

The technology, referred to as the "Toolbox for the Structural Analysis of Narratives," includes two distinct computer programs that generate visualizations of narrative texts. These visualizations are the Scatter Plot of Entities and the Narrative Flow Graph. The purpose of these tools is to assist analysts in understanding and evaluating narratives by automatically identifying key structural elements, thus addressing the complex and time-consuming nature of manual narrative analysis.

Scatter Plot of Entities: This visualization helps users to:

  • Partition the story into scenes.
  • Mark locations of plot importance.
  • Identify the most influential entities in the story.
  • Understand when entities are active in the story and with which other entities.

Narrative Flow Graph: This visualization enables users to:

  • Infer the story location of scenes where the location is not explicit.
  • Decompose events into scenes.
  • Track entities through the story by following the scenes they appear in.
  • Visualize the overall narrative structure, such as branching or parallel tracks in the story.
  • Understand the scenes that are plot-important, including visualizing the story's climax.

These visualizations are designed to maximize insight into the underlying story while being as close to completely automatic as possible. This technology offers a unique approach by characterizing the overall arc of a narrative, unlike tools such as social network extraction, event extraction, or sentiment analysis, which focus on isolated elements.

Marketing Plan

1. Target Audience:

  • Academic and Research Institutions: Universities and research institutions focused on literature, linguistics, and media studies.
  • Media and Entertainment Industry: Writers, script editors, and producers seeking tools to analyze narrative structures.
  • Publishing Houses: Editors and publishers who need tools to assess manuscripts efficiently.
  • Marketing and Advertising Agencies: Agencies that need tools for creating compelling brand stories.
  • Educational Technology Companies: Firms looking for innovative educational tools in literature and creative writing.
  • Content Creators: Freelance writers, educators, or small teams who prefer self-service options.

2. Marketing Channels:

  • Direct Sales: Engage directly with large organizations like universities, research institutions, and major publishers through a dedicated sales team.
  • Distributors and Resellers: Partner with distributors specializing in software solutions for education and creative sectors.
  • Online Platforms: Offer the tools through an online platform where users can purchase licenses or subscriptions, integrating with software marketplaces and educational platforms.
  • Partnerships with Educational Institutions: Collaborate with universities to integrate these tools into their curricula. Offer workshops and seminars.
  • Workshops and Conferences: Host workshops at industry-specific events related to storytelling, data visualization, and AI.
  • Content Marketing: Develop blog posts, white papers, webinars, and video content to illustrate the unique insights provided by the visualizations.
  • Social Media Campaigns: Use social media platforms to showcase the technology's advantages over existing solutions.
  • Targeted Content Marketing: Develop content that demonstrates how these visualizations solve specific problems in narrative analysis.
  • Educational Webinars and Workshops: Host webinars and online courses to educate potential users on the effective use of the tools.
  • Influencer Collaborations: Partner with influencers in fields such as storytelling or digital humanities to showcase the tool's capabilities.
  • Trade Shows and Conferences: Present the technology at relevant industry conferences and trade shows.
  • SEO and Online Advertising: Optimize website content for search engines and use targeted online advertising campaigns.
  • Community Building: Create an online community forum for users to share tips and best practices.

3. Marketing Strategies:

  • Highlight Unique Advantages: Emphasize the ability to automatically analyze the overall arc of a narrative, unlike other tools such as social network extraction or sentiment analysis.
  • Showcase Practical Applications: Use case studies to demonstrate how the visualizations provide unique insights and improve efficiency.
  • Offer Freemium Model/Free Trial: Implement a freemium model or free trial to allow potential customers to experience the benefits firsthand.
  • Focus on Efficiency Gains: Emphasize how this technology significantly reduces the time and effort required to evaluate complex narratives.
  • Emphasize Enhanced Insights: Showcase the ability of the technology to provide deeper insights than traditional methods, leading to better decision-making.
  • Competitive Advantage: Market the technology as offering a competitive edge in understanding narrative arcs.

Commercialization Plan

1. Business Model

  • Subscription Model: This model is most suitable, offering a Software-as-a-Service (SaaS) platform where customers pay regularly for access to the tool, updates, and support. This model will appeal to businesses or researchers who frequently analyze narratives and want continual access to updated features.
  • Licensing Model: For large organizations or institutions that prefer one-time payments, a licensing model can be offered.

2. Revenue Streams

  • Software Licensing: License the core technology to businesses, educational institutions, or media companies.
  • Subscription Model: Offer the technology through a cloud-based platform with different subscription tiers based on functionality.
  • Consulting Services: Provide expert consulting services using the technology to help organizations interpret complex narratives.
  • Integration with Existing Tools: Partner with companies offering complementary technologies to create cross-selling opportunities.
  • Educational Tools and Resources: Develop educational materials for academic institutions.
  • Customized Solutions: Tailor solutions for specific industries such as entertainment or publishing.
  • Data Analysis Services: Offer services where data is analyzed to extract meaningful insights.
  • Collaborations with Content Platforms: Partner with platforms to enhance their content recommendation systems.
  • Maintenance Contracts: Offer regular software updates to ensure compatibility with new data formats.
  • Support Services: Provide technical support, training sessions, and troubleshooting assistance.
  • Upgrades and Enhancements: Offer upgrades to access enhanced capabilities and new features.
  • Customization Services: Offer tailored visualizations for specific sectors.
  • Training and Workshops: Conduct workshops on how to effectively use the visualization tools.

3. Pricing Strategy

  • Value-Based Pricing: Set prices based on the perceived value to the customer, particularly for those who analyze large volumes of narrative text.
  • Tiered Pricing: Offer different pricing tiers based on features or usage levels, catering to a wide range of customer segments.
  • Subscription Model: Offer subscription plans for continuous updates and support.
  • Freemium Model: Provide a basic version for free to attract users who may convert to paying customers.
  • Enterprise Licensing: Offer volume discounts for large organizations.
  • Consultancy Services Add-on: Offer consultancy services as an additional purchase option.
  • Educational Discounts: Offer discounts for educational institutions.

4. Financial Considerations

  • Initial Investment Costs: This includes research and development, software development, and marketing expenses.
  • Operational Costs: Account for ongoing operational costs such as maintenance, customer support, and hosting.
  • Funding Needs: Early-stage commercialization could range from $500,000 to several million dollars.
  • Projected Development Costs: Development could range from hundreds of thousands to millions of dollars, depending on complexity and scale.
  • Return on Investment: The combination of efficiency gains, enhanced insights, competitive advantages, and scalability suggests a promising ROI.

5. Intellectual Property Strategy

  • Patent Protection: Secure patents for unique methods and algorithms used in generating the visualizations.
  • Copyright: Protect the software code used to implement the system.
  • Trade Secrets: Safeguard proprietary algorithms or processes not publicly disclosed.
  • Trademarks: Protect distinctive names or branding associated with the visualization tools.
  • Freedom-to-Operate Analysis: Conduct a freedom-to-operate analysis to assess whether commercializing a similar product would infringe on existing IP rights.
  • Licensing Agreements: If needed, consider licensing agreements with patent holders for overlapping technologies.

6. Market Entry Strategy

  • Prioritize Initial Markets: Target academic and research institutions, media and entertainment industries, and publishing houses.
  • Regions with Strong Tech Adoption: Focus on regions with strong technological infrastructures, such as North America and Europe.
  • Phased Approach: Consider initial deployment in less regulated markets before entering more heavily regulated regions.

7. Strategic Partnerships

  • Publishing Industry: Partner with publishing software companies to integrate the visualizations into editorial workflows.
  • Film and Television Production: Partner with screenwriting software developers to create tools for scriptwriters.
  • Education Technology Companies: Collaborate with EdTech firms to integrate the visualizations into their platforms.
  • Gaming Industry: Partner with video game developers to enhance storytelling in games.
  • Data Analytics Firms: Collaborate with companies specializing in text analysis or natural language processing.
  • AI Research Labs: Partner with AI researchers working on improving machine understanding of narratives.

8. Funding Opportunities

  • National Science Foundation (NSF): Explore grants supporting research in computer science, AI, and data visualization.
  • European Research Council (ERC): For projects based in Europe, explore grants supporting innovative projects.
  • Defense Advanced Research Projects Agency (DARPA): If applicable, explore funding for applications related to national security or defense narratives analysis.
  • Horizon Europe: Seek EU funding for projects focused on digital transformation.
  • Private Foundations: Explore funding from organizations that support technological innovations.
  • Tech Industry R&D Funding: Look for research grant programs from tech companies like Google, Microsoft, or IBM.
  • SBIR/STTR Programs: Explore funding for small businesses engaged in federal R&D with commercialization potential.
  • Academic Institution Grants: Look into universities that offer internal grants.
  • Crowdfunding Platforms: Consider platforms like Kickstarter or Indiegogo to raise funds.

9. Regulatory Considerations

  • Data Privacy and Protection: Comply with regulations like GDPR and CCPA if processing personal data.
  • Intellectual Property Rights: Ensure the right to process narrative texts, obtaining necessary licenses.
  • Content Moderation and Compliance: Comply with content moderation standards when applicable.
  • Accuracy and Bias Mitigation: Ensure the technology does not introduce bias in analyses.
  • Export Control Laws: Be aware of export control laws if distributing software internationally.

The "Toolbox for the Structural Analysis of Narratives" comprises two distinct computer programs that generate visualizations of narrative texts: the Scatter Plot of Entities and the Narrative Flow Graph. These tools automatically analyze narratives, addressing the difficulty and time-consuming nature of manual evaluation. The Scatter Plot of Entities helps analysts partition a story into scenes, mark locations of plot importance, and identify influential entities, including when they are active and with whom. The Narrative Flow Graph allows analysts to infer scene locations (even when not explicit), decompose events into scenes, track entities across scenes, visualize overall narrative structure (including branching or parallel tracks), and understand plot-important scenes, including the climax. These visualizations are designed to maximize informativity and insight about the underlying story while being as close to completely automatic as possible. The core innovation lies in the automated, comprehensive visualization of the overall narrative arc, not just isolated elements. This differentiates it from technologies like social network extraction or sentiment analysis.

Phase 1: Understanding the Technology and its Potential

  • Deep Dive into the Technology: Fully understand the capabilities of both the Scatter Plot of Entities and the Narrative Flow Graph. Know how each visualization is generated, what problems it solves, and the specific insights they provide.
  • Identify the Core Innovation: Recognize that the core innovation lies in the automated, comprehensive visualization of the overall narrative arc, not just isolated elements. This is a key differentiator from existing tools like social network extraction or sentiment analysis.
  • Recognize the Target Market: Identify potential users including literary analysts, authors, educators, media professionals, game developers, and business analysts. Understand their specific needs and how the technology can help them.
  • Understand the tech’s value proposition: The technology’s value comes from its ability to provide automated insights, reduce manual analysis, offer comprehensive views of narrative structures, and enhance storytelling capabilities. It addresses the complexity and time-consuming nature of manual narrative evaluation by providing comprehensive insights into story arcs.

Phase 2: Intellectual Property and Legal Considerations

  • Patent Search: Conduct a thorough patent search to identify any existing patents related to the technology. This involves searching databases like USPTO and EPO using relevant keywords.
  • Freedom-to-Operate Analysis: Assess whether commercializing a similar product would infringe on existing IP rights. This involves evaluating both direct and indirect infringement risks.
  • Secure IP Protection: If the technology is novel, pursue patent protection for the specific methods and systems involved in generating the visualizations. Also consider copyright for the software code and trademarks for any distinctive names associated with the tools.
  • Data Privacy Compliance: Ensure compliance with data protection regulations like GDPR or CCPA if processing personal data.

Phase 3: Business Model and Market Strategy

  • Choose a Business Model: The subscription model is most suitable for this technology given its SaaS potential. It provides a steady revenue stream and encourages continuous engagement. Consider tiered pricing to cater to different user needs.
  • Develop a Marketing Strategy: Create a multi-channel marketing approach targeting different segments of potential users. This should include direct sales, online platforms, educational partnerships, workshops, and content marketing.
  • Prioritize Initial Markets: Focus on academic and research institutions, the media and entertainment industry, and publishing houses. These sectors have a high demand for narrative analysis tools. Target regions with strong tech adoption like North America and Europe.
  • Pricing: Implement a value-based pricing strategy, considering tiered pricing, subscription models, and freemium options. You may also offer consultancy services as an add-on.

Phase 4: Development and Refinement

  • Enhance the Technology: Improve the robustness, accuracy, and scalability of the algorithms. Ensure the system can handle large volumes of text efficiently.
  • Address Technical Challenges: Be prepared to address technical hurdles such as natural language processing, entity recognition, and handling non-linear narratives.
  • Design User Interface: Develop an intuitive user interface that allows users to interact effectively with the visualizations.
  • Establish Feedback Mechanisms: Implement mechanisms for users to provide feedback on visualization accuracy to help iteratively improve system performance.
  • Integration Capabilities: Ensure the technology can be integrated with existing tools used by analysts, through APIs or plugins.

Phase 5: Launch and Growth

  • Pilot Programs: Offer pilot programs to selected organizations for feedback on usability and accuracy. This real-world testing is essential before a wider release.
  • Early Adopters: Engage with early adopters, such as researchers, journalists, or educators to get insights into practical applications.
  • Seek Funding: Explore funding opportunities and grants from sources like NSF, ERC, or private foundations. Consider SBIR/STTR programs.
  • Build a strong team: Assemble a team of software developers, data scientists, UI/UX designers, marketing experts, and legal advisors.
  • Plan for scalability: Consider the costs associated with cloud resources, data storage, software development and maintenance, personnel, marketing and R&D as you scale up.
  • Monitor Performance and ROI: Track user engagement and other key performance indicators. Use this data to continuously improve the technology and your marketing strategies. Conduct breakeven analyses, and use the data to adapt your strategy if necessary.

Key Considerations for the Student Entrepreneur:

  • Focus on the unique value: Emphasize the unique capabilities of the technology in providing a comprehensive view of narrative structures that other tools cannot offer.
  • Be aware of market risks: Be aware of and mitigate risks related to market adoption, competition, intellectual property, and data privacy.