Automatic Estimation of Web Bloggers’ Age Using Regression Models

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title = "Automatic Estimation of Web Bloggers{\textquoteright} Age Using Regression Models",
abstract = "In this article, we address the problem of automatic age estimation of web users based on their posts. Most studies on age identification treat the issue as a classification problem. Instead of following an age category classification approach, we investigate the appropriateness of several regression algorithms on the task of age estimation. We evaluate a number of well-known and widely used machine learning algorithms for numerical estimation, in order to examine their appropriateness on this task. We used a set of 42 text features. The experimental results showed that the Bagging algorithm with RepTree base learner offered the best performance, achieving estimation of web users{\textquoteright} age with mean absolute error equal to 5.44, while the root mean squared error is approximately 7.14.",
keywords = "Author{\textquoteright}s age estimation, Text processing, Regression algorithms ",
author = "Vasiliki Simaki and Christina Aravantinou and Iosif Mporas and Vasileios Megalooikonomou",
year = "2015",
doi = "10.1007/978-3-319-23132-7_14",
language = "English",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "113--120",
editor = "Andrey Ronzhin and Rodmonga Potapova and Nikos Fakotakis",
booktitle = "Speech and Computer",
address = "Germany",