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Distance Measures. The Indiana team identified additional bots by computing the cosine similarity between users and known bots. Figure 4 shows the kernel density estimation of the pairwise cosine distance between pairs of feature vectors characterizing two bots, compared to bot-human pairs. The distances between bot pairs are much smaller than bot-human pairs. The bot-bot distance exhibits a bimodal distribution that reflects the presence of two types of bots designed by two teams. Sentimetri: achieved similar success using Jaccard distance.  distance between pairs of feature vectors characterizing two bots, compared to bot-human pairs. The

Figure 4 Distance Measures. The Indiana team identified additional bots by computing the cosine similarity between users and known bots. Figure 4 shows the kernel density estimation of the pairwise cosine distance between pairs of feature vectors characterizing two bots, compared to bot-human pairs. The distances between bot pairs are much smaller than bot-human pairs. The bot-bot distance exhibits a bimodal distribution that reflects the presence of two types of bots designed by two teams. Sentimetri: achieved similar success using Jaccard distance. distance between pairs of feature vectors characterizing two bots, compared to bot-human pairs. The