AITSteg: An Innovative Text Steganography Technique for Hidden Transmission of Text Message via Social Media

High capacity steganography tool for Arabic text using 'Kashida'

Steganography is the ability to hide secret information in a cover-media such as sound, pictures and text. A new approach is proposed to hide a secret into Arabic text cover media using "Kashida", an Arabic extension character. The proposed approach is an attempt to maximize the use of "Kashida" to hide more information in Arabic text cover-media. To approach this, some algorithms have been des...

Text Analytics in Social Media

The rapid growth of online social media in the form of collaborativelycreated content presents new opportunities and challenges to both producers and consumers of information. With the large amount of data produced by various social media services, text analytics provides an effective way to meet usres’ diverse information needs. In this chapter, we first introduce the background of traditional...

Content modeling for social media text

This thesis focuses on machine learning methods for extracting information from usergenerated content. Instances of this data such as product and restaurant reviews have become increasingly valuable and influential in daily decision making. In this work, I consider a range of extraction tasks such as sentiment analysis and aspect-based review aggregation. These tasks have been well studied in t...

Sentence Boundary Detection for Social Media Text

The paper presents a study on automatic sentence boundary detection in social media texts such as Facebook messages and Twitter micro-blogs (tweets). We explore the limitations of using existing rule-based sentence boundary detection systems on social media text, and as an alternative investigate applying three machine learning algorithms (Conditional Random Fields, Naïve Bayes, and Sequential ...

A New Segmentation Technique for Omnifont Farsi Text