Languages shared by people differs due to diversity in their ethnicity, socioeconomic status, gender, language, religion, sexual orientation, geographical area, accents, pronunciation and word usages. This eventually fall into hypothesis that they follow unknown hidden pattern. By using this hypothesis, determining the class of a person such as age, gender, their personality and nativity has mu...

Author profiling is the task of determining the age, gender or type of the author's personality by studying their sociolect aspect, that is, how the language is shared by people. This paper presents the COMSATS Institute of Information Technology, Lahore entry for the PAN 2015 competition on Author Profiling task. Our proposed system is based on stylometry features. We implemented 29 different ...

Our work on author identification and author profiling is based on the question: Can the number and the types of grammatical errors serve as indicators for a specific author or a group of people? In order to detect the grammatical errors we base our approach on the output of the open-source library LanguageTool. In the case of the author identification we transform the problem into a statistica...

This paper reports on the PAN 2014 evaluation lab which hosts three shared tasks on plagiarism detection, author identification, and author profiling. To improve the reproducibility of shared tasks in general, and PAN’s tasks in particular, the Webis group developed a new web service called TIRA, which facilitates software submissions. Unlike many other labs, PAN asks participants to submit run...

This paper presents an approach for author profiling of an unknown users from their texts produced in social media. In particular, we address the identification of two profile dimensions: gender and language variety, of Arabic twitter users based on their tweets. Our approach focused on applying metaclassification technique on features extracted from tweets body. We explored two main sets of fe...

In this paper, we describe one of the approaches of the participation of Universidade de Évora. Our approach is similar to usual methods where text is preprocessed, features are extracted, and then used in SVMs with cross validation. The main difference is that features used come from averages of word embeddings, specifically word2vec vectors. Using PAN 2016 dataset, we were able to achieve 44....

In this paper, we describe a method for the detection of plagiarism based on author profiling [1]. After having segmented a document into a set of texts, we apply the technique of predicting the age and gender of the author on these texts. In case the predictions are heterogeneous, the probability of the existence of plagiarism becomes really great. Predicting the gender and age of the author w...

This paper illustrates work done on "Gender Identi cation in Russian texts (RusPro ling)" shared task, hosted by PAN in conjunction with FIRE 2017. The task is to predict the author’s gender, based on the Twitter data corpus which is in Russian. We will give a brief introduction to the task at hand, elaborate on the data-set provided by the competition organizers, discuss various feature select...

Author profiling, being an important problem in forensics, security, marketing, and literary research, needs to be accurate. With massive amounts of online text readily available on which we might need to perform author profiling, building a fast system is as important as building an accurate system, but this can be challenging. However, the use of distributive computing techniques like MapRedu...

This overview presents the framework and results for the Author Profiling task at PAN 2013. We describe in detail the corpus and its characteristics, and the evaluation framework we used to measure the participants performance to solve the problem of identifying age and gender from anonymous texts. Finally, the approaches of the 21 participants and their results are described.