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And, obviously, it is unknown to which degree the information that is present is true.The resource would become even more useful if we could deduce complete and correct metadata from the various available information sources, such as the provided metadata, user relations, profile photos, and the text of the tweets.Their features were hash tags, token unigrams and psychometric measurements provided by the Linguistic Inquiry of Word Count software (LIWC; (Pennebaker et al. Although LIWC appears a very interesting addition, it hardly adds anything to the classification.

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With lexical N-grams, they reached an accuracy of 67.7%, which the combination with the sociolinguistic features increased to 72.33%. (2011) attempted to recognize gender in tweets from a whole set of languages, using word and character N-grams as features for machine learning with Support Vector Machines (SVM), Naive Bayes and Balanced Winnow2.

Their highest score when using just text features was 75.5%, testing on all the tweets by each author (with a train set of 3.3 million tweets and a test set of about 418,000 tweets). (2012) used SVMlight to classify gender on Nigerian twitter accounts, with tweets in English, with a minimum of 50 tweets.

However, as any collection that is harvested automatically, its usability is reduced by a lack of reliable metadata.

In this case, the Twitter profiles of the authors are available, but these consist of freeform text rather than fixed information fields.

The authors do not report the set of slang words, but the non-dictionary words appear to be more related to style than to content, showing that purely linguistic behaviour can contribute information for gender recognition as well.

Gender recognition has also already been applied to Tweets. (2010) examined various traits of authors from India tweeting in English, combining character N-grams and sociolinguistic features like manner of laughing, honorifics, and smiley use.

So, take a stroll down memory lane to remember all of our past Word of the Year selections.

by Michele Picozzi Whether or not you take drugs to suppress future outbreaks of HSV-1 (facial herpes) and HSV-2 (genital herpes), to get outbreaks under control a strong immune system is necessary.

We often sacrifice sleep, regular meals, and exercise in pursuit of our goals.

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