1. A method comprising: aggregating, from a set of points extracted from a large document, a set of core points, a point and a core point each being a topic covered in the document; constructing, for the core point in the set of core points, a network of associations, wherein an association in the network comprises an entity that has a relationship with the core point by virtue of having contributed data in the document that relates to the core point; computing, from the contributed data a sentiment value of the contributed data, the sentiment value being indicative of a sentiment of the entity towards the core point; analyzing a data stream from a data source other than the document to isolate a portion of data stream that relates to the core point; identifying a second entity in the portion of the data stream, wherein the second entity contributes the portion of the data stream that relates to the core point; computing, from the portion of the data stream that relates to the core point, a second sentiment value of the second entity towards the core point; determining that the second entity does not exist in the network of associations; adding, responsive to determining that the second entity does not exist in the network of associations, the second entity and the second sentiment value to the network of associations; computing from a set of sentiment values corresponding to the associations in the network of associations, an overall sentiment value for the core point; and reporting overall sentiment values for each core point in the document.
2. The method of claim 1 , further comprising: analyzing the document to identify a first set of entities, wherein the entities in the first set of entities participate in the document relative to the core point, the entities from first set of entities being used in the network of associations.