Gibsonian Echoes: Narrative Resonance Tracker

Inspired by the rich, speculative fiction of 'Neuromancer' and the grand, data-driven exploration of 'Interstellar,' this project leverages Natural Language Processing (NLP) to create a 'Map Locations' style analytical scraper. The core idea is to identify and quantify stylistic and thematic 'resonances' of 'Neuromancer' within a corpus of contemporary text. This could include online forums, news articles, blog posts, and even snippets from other novels. The system will employ techniques like topic modeling, sentiment analysis, and word embedding comparison (e.g., using pre-trained models like Word2Vec or GloVe) to detect recurring patterns, specific vocabulary, and narrative structures reminiscent of Gibson's seminal work. Think of it as charting the linguistic 'graffiti' of 'Neuromancer' across the digital landscape. The niche lies in its focused approach to literary influence tracking within the realm of speculative fiction's impact on general discourse. Implementation is low-cost, relying on readily available NLP libraries (like NLTK, spaCy, Gensim) and open-source text data. High earning potential can be realized by offering this analysis as a service to literary critics, academics, writers studying genre evolution, and even market researchers looking for emerging cultural trends and influencer language patterns. The 'Interstellar' element comes in the ambition to chart vast linguistic territories and uncover hidden connections, much like navigating the cosmos through data. The output could be visualized as a series of thematic maps or trend graphs, highlighting specific 'Gibsonian' clusters within the text corpus.