A corpus-based lexical network for measuring topic alignment of forum messages - Rage, Rodulfo Jr. C. (Philippine computing journal)
This paper present a proposed methodology for the analysis of the topical alignment of forum messages. Aspects of the semantic representation provided by Random Indexing are combined with some statistical properties of words in text to generate a lexical network which we believe represents a topical structure of text. This approach allows assessment of the degree to which the topic of message is relevant to the topic of an external reference document. Analysis is done using procedures adapted from the Lesk work overlap algorithm. Application of this approach to messages in a discussion transcript with manually assigned topical alignment values indicate that the performance of the system is still below the average inter-rater reliability of human coders, however, its performance can still be enhanced by exploiting other resources. We also believe that the results obtained in the experiments have raised a number of points which may be worthy of future investigation. We provide some findings and suggestions from the literature that we deem supports our conjecture.