Online newspaper articles can accumulate comments at volumes that prevent close reading. Summarisation of the comments allows interaction at a higher level and can lead to an understanding of the overall discussion. Comment summarisation requires topic clustering, comment ranking and extraction. Clustering must be robust as the subsequent extraction relies on a good set of clusters. Comment data, as with many social media datasets, contains very short documents and the number of words in the documents is a limiting factors on the performance of LDA clustering. We evaluate whether we can combine comments to form larger documents to improve the quality of clusters. We find that combining comments with comments that reply to them produce the highest quality clusters.
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