User:Sikubernetes
Project Introduction
[edit]Hello, fellow Wikipedians!
I've embarked on an exciting project that explores a new way of understanding and analyzing our knowledge graph here on Wikipedia. I'm applying Natural Language Processing (NLP) techniques to extract insights from the inbound links (or inlinks) of a Wikipedia page, a concept I've named the "Inlinking Problem".
The Inlinking Problem
[edit]Typically, when we consider hyperlinks on a Wikipedia page, we think about where these links lead to - these are outbound links. However, each page also has a multitude of inlinks - links from other pages that point towards it. These inlinks can offer a wealth of untapped insights, revealing the contexts in which the page's subject is discussed elsewhere on Wikipedia.
My aim is to utilize NLP techniques to aggregate and interpret this inlink data, effectively creating an "inlink profile" for a page. This process, when applied across Wikipedia, results in an undirected graph from the original directed graph, leading to a more comprehensive understanding of the interconnections within Wikipedia.
Benefits and Applications
[edit]This approach could provide a myriad of insights, such as:
- Alternative Perspectives: Observing the different contexts in which a page is linked could provide a variety of perspectives on a single subject.
- Conflict and Controversy Detection: Contrasting viewpoints or controversial aspects of a topic could become apparent when examining inlinks.
- Semantic Understanding: Analyzing the text surrounding inlinks could enhance our semantic understanding of a topic.
Your Thoughts
[edit]I'd love to hear your thoughts, feedback, and suggestions on this project. How do you see this approach enhancing our understanding of Wikipedia's knowledge graph? Can you envision any potential applications or implications that I haven't mentioned?
Collaboration Opportunities
[edit]If you're interested in this project and would like to collaborate or contribute in any way, please feel free to reach out. I believe that with the combined efforts of our community, we can make significant strides in unearthing new layers of insights from our vast collection of knowledge here on Wikipedia.