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Are they mostly targeting the content of the tweets, i.

In addition, the recognition is of course also influenced by our particular selection of authors, as we will see shortly. Speed dating wien studenten TiMBL is currently underperforming, but might be a challenger to SVR when provided with a better hyperparameter selection mechanism.

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This corpus has been used extensively since. Even the character 5-grams have ranks up to 40 for this top We start with the accuracy of the various features and systems Section 5. It then chose the class for which the final score is highest.

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We will illustrate the options we explored with the Hahaha We achieved the best results, Several errors could be traced back to the fact that the account had moved on to another user since We could have used different dividing strategies, but chose balanced folds in order to give a equal chance to all machine learning techniques, also those that have trouble with unbalanced data.

Gender recognition has also already been applied to Tweets.

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This apparently Songs about dating your ex not only the discussion topics, which might be expected, but also the general language use.

Finally, we included feature types based on character n-grams following kjell et al. When using all user tweets, they reached an accuracy of We will only look at the final scores for each combination, and forgo the extra detail of any underlying separate male and female model scores which we have for SVR and LP; see above.

Taking again SVR on unigrams as our starting point, this group contains 11 males and 16 females. We also varied the recognition features provided to the techniques, using both character and token n-grams.

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The dashed line represents the separation threshold, i. With these main choices, we performed a grid search for well-performing hyperparameters, with the following investigated values: However, even style appears to mirror content.

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However, we used two types of character n-grams. LP keeps its peak at 10, but now even lower than for the token n-grams As scaling is not possible when there are columns with constant values, such columns were removed first.


After this, we examine the classification of individual authors Section 5. On the female side, we see a representation of the world of the prototypical young female Twitter user.

Experimental Data and Evaluation In this section, we first describe the corpus that we used in our experiments Section 3. Top rankingfemales insvr ontokenunigrams, with ranksand scoresforsvr with various feature types.

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One gets the impression that gender recognition is more sociological than linguistic, showing what women and men were blogging about back in A later study Goswami et al. Interestingly, it is SVR that degrades at higher numbers of principal components, while TiMBL, said to need fewer dimensions, manages to hold on to the recognition quality.

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Even so, there are circumstances where outright recognition is not an option, but where one must be content with profiling, i. However, we received confirmation that she writes almost all her tweets herself Sargentini, personal communication.

URLs and addresses are not completely covered.

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Feature type Unigram 1: For the other feature types, we see some variation, Speed dating wien studenten most scores are found near the top of the lists.

Possibly, the other n-grams are just mirroring this quality of the unigrams, with the effectiveness of the mirror depending on how well unigrams are represented in the n-grams.

Furthermore, LP appears to suffer some kind of mathematical breakdown for higher numbers of components. Bigrams Two adjacent tokens. The class separation value is a variant of Cohen s d Cohen