"ppl", "under", "bad", "jornada", "god", "home", "trending", "seeing", "living", "crying", "nada", "trend", "everything", "saudara", "sin", "pain", "horrible", "solo", "real", "Palestine", "remember", "Bashar", "bombed", "día", "look", "Jesus", "eyes", "power", "strikes", "hear", "mais", "chemical", "picture", "stand", "poor", "million", "vida", "government", "situation", "tweet", "tears", "wrong", "hacer", "triste", "watching", "porque", "cry", "word", "mean", "sleep", "night", "enough", "amor", "victims", "money", "done", "man", "affected", "untuk", "again", "mercy", "happen", "yet", "cruel", "moment", "year", "poder", "hurts", "estamos", "humans", "parar", "understand", "imagine" ] #":(", ":'(" # Calculates most used words in tweets: fetchy.calculateMostUsed(700) #, smooth=12000) # Recovers only wanted words: fetchy.filterMostUsed(chosenWords) # Saves data to JSON file: fetchy.jsonMostUsed(20) # Obtains a dictionary where words are keys and values are how many times they appear in the tweet texts: #frequenciesDict = fetchy.getMostUsed(); # Initializes Word Cloud using the frequency dictionary: #disp = Display(frequenciesDict, maskPath="Visualization/img/machine_gun.png") # Creates an image: #disp.produceImage("Visualization/syria.png")