As was stated by others before, I find the name very misleading. I know "Higher Order Tensors Toolbox" sounds way cooler than "ndarray toolbox", but wouldn't the second one be closer to the truth?
Furthermore, if 1-D Arrays are called vectors, and 2-D Arrays are called Matrices and 3-D (or higher) Arrays are called Tensors, does that not automatically mean that every Tensor is higher order? ...
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Hello yigit, Actually I did consider it. In short; out of the >200.000 users who posted Tweets regarding politics in the period of 1 May to 06 June there were a few dozen users who posted thousands of Tweets instead of only a few (<10). However, because there are only a few dozen users like this in a total set of >200.000 users, their actions do not affect the result much.
Unfortunately I did not have enough time to do a similar analysis on the Twitter data from Oktober. But I hope that the same conditions apply. In any case, I will take your concerns into account and try to do more analysis on the set of users from the dataset of September and Oktober if I have some time today or tomorrow.
yes I believe that some parties will be overrepresented if you solely look at the volume of tweets. This is simply due to the fact that Twitter in Turkey is more popular under young and educated people(1). It should however not be difficult to take this into account in the linear regression algorithm, because the tuning parameters can be determined with data from the previous elections.
I had made an prediction for each province after initially collecting all the tweets, but the results were not accurate. At the moment I have also determined the location of about 33% of the twitter accounts and I hope the result will be better if I exclude all Twitterers which are not from the same province as the one I am doing the calculation on.
For nearly a century it was only possible to find out what the general public thinks with traditional polling, which costs thousands or even millions of dollars/euros. Since the rise of Web 2.0 Social Media analytics has been increasingly popular. A lot has been said about the predictive power of Twitter so far. According to some people you should be able to predict flu epidemics, unemployment and even riots/revolutions. What about Elections?
I have tried to predict the outcome of Turkish General elections of 1 November 2015 using Twitter data and I believe I will be able to predict quiete accurately. Within a few percent.
Furthermore, if 1-D Arrays are called vectors, and 2-D Arrays are called Matrices and 3-D (or higher) Arrays are called Tensors, does that not automatically mean that every Tensor is higher order? ...