I have am working on a project where I have seven “posts.” The posts are just a sentence or two about the subject. What I need to do is to develop an algorithm which looks through the posts and identifies certain trends.
For example, “A is good but causes B.” I need to develop an algorithm which would identify the link between A and B.
However, as you may be able to tell from my sub par description, I have no idea how to address this problem. Can anybody point me in the right direction? I looked at data mining but I’m not sure if that is what I need.
What you are asking is a hot research topic in text mining and natural language processing. However, your question is too general imo.
The simplest thing you could start with might be identifying the words that frequently appear together in a sentence (or consecutive sentences). That would at least provide you with some kind of a correlation. Look into Association Rule Learning as user1161595 suggested. Clustering techniques might be of help too. To begin with, have a look at cluster analysis and text clustering.
To extract relationships between the words, you need to dive deep into natural language processing. You can use Google Scholar for searching related research on text mining, trend analysis and information retrieval.
In addition, the following links might give you an idea of what you are dealing with:
As for the implementation, you might look into the open source frameworks mentioned on Wikipedia. Furthermore, there are lots of machine learning and NLP libraries out there.
Last but not least, I believe there is a good chance that something similar to what you are looking for has already been implemented somewhere by someone. So a through Google search with the right keywords might get you what you want without diving deep into research.