Classification of internet memes
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This paper explores a system that could be used to classify internet memes by certain characteristics. The anatomy of these viral images are explored to find the best indicators to classify an internet meme. Although more than one indicator was found, the paper focuses on the using image data to perform the classification. Further research is done to determine which type of feature descriptor would be used based on past successes of other projects. A dataset is a scraped from a popular repository of memes on the internet and their features extracted. Features are passed into a SVM classifier to derive a unique listing of potential labels that an image could have. Although training times were very reasonable as the number of classes increased, result accuracy degrade with increase in number of classes trained on the same model.