суббота, 25 мая 2013 г.

Tweets mining using NLP can help in goods marketing.

   Recently the topic of data mining of messages in social networks, particularly in Twitter, has been widely discussed, from the point of view of sociology, politics, economics, marketing, etc.

  In this study, I want to show that tweets mining  can be valuable for the marketing research of goods. I took smartphones as an example. I have downloaded several thousands of tweets that refer to smartphones and contain the keywords like: iPhone, Apple, Galaxy, Blackberry, etc.  To study the iPhone concept, we used the theory of frequent sets and association rules. The research was conducted using the language of statistical calculations R.
Here are the results obtained:

 We received a matrix for aggregated association rules for concept 'iphone':


The association rules for concept 'iphone' with high support can be represented with the help of such graphs:



The frequent sets for concept 'iphone' with the high value of support can be represented by the following graphs:



Here is an example of associations for different smartphones :


The popularity of different models:

The comparison of two models based on tweets mining, using syntactic parsing:


5 комментариев:

  1. Hello,

    I'm curious, what tools are you using to retrieve such informations, is it open-source ?

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    1. Hi François-Guillaume,
      it is R language with additional packages, more info about R you can find at http://www.r-project.org
      Thnaks,
      Bohdan

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  2. Hi Francois,

    I think it was the R programming language (Open-source).

    Bohdan, how did you download all those tweets? I tried to do the same once using the TwitteR package and even specifying that I wanted 1000 tweets I was able to download in groups of less than 100. I did the OAth autentication for the twitter API but it did not seem to work.

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    1. Hi Orlando,
      you need to specify max number of tweets,
      also if you try to load the same tweets second time then you will be able to load the small number of tweets
      Thanks,
      Bohdan

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  3. Hi Bohdan,
    Thanks for exiting studies.
    I would like to invite you to write a short article about your system/share your experience on tweets analysis for the NLP People website ( www.nlppeople.com ) that I'm managing. If you think it can be of interest for you, we can discuss possible layout of the article by email or during a skype call. My email address is maxim@nlppeople.com
    Looking forward to hearing from you,
    Maxim

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