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Analyze the text conversations exported from Whatsapp or any other messaging tools using Natural Language Processing techniques.

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One can obtain the text conversations from WhatsApp by clicking on a person's profile in conversation window and -> Export Chat, lets name it "_chat.txt".

Though only parser to extract texts from WhatsApp conversations is implemented currently. The techniques used here can be extended to any kind of mesaging platforms which allow users to download their conversations

First convert the chat file into list of instances of Message making sure that the order of conversation is preserved.

from message import read_whatsapp_chat_file
messages = read_whatsapp_chat_file('_chat.txt')

We can pass the list of Message objects to Analyze class and calculate various stats that are pre-implemented. The methods implemented for calculation of stats are agnostic to the messaging platform, because the data structure they use is Message.

from analyze import Analyze

chat = Analyze(messages)
print(chat.number_of_messages)
print('--------------------------')
print(chat.number_of_words)
print('--------------------------')
print(chat.number_of_questions)
print('--------------------------')
print(chat.n_frequent_words)
print('--------------------------')
print(chat.common_words)
print('--------------------------')
print(chat.one_word_replies)
print('--------------------------')
print(chat.average_resp_times)
print('--------------------------')
print(chat.max_delays)
print('--------------------------')
print(chat.nr_conv_starts)
print('--------------------------')
print(chat.nr_emojis)
print('--------------------------')
print(chat.emojis)
print('--------------------------')
print(chat.common_emojis)
print('--------------------------')
print(chat.nr_unique_emojis)
print('--------------------------')
print(chat.nr_messages_per_window)
print('--------------------------')

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Analyze the text conversations exported from Whatsapp or any other messaging tools using Natural Language Processing techniques.

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