Dear Colleagues,

Twenty years ago, it was estimated that 80% of information was transmitted in a text format. Considering the value of the information contained in a text, text mining techniques began to be developed to process large volumes of writing and extract valuable knowledge for decision makers. With the advances in information and communication technologies, the amount of information in textual outputs has likely increased considerably as of now. In addition, the rise of social media and content platforms have become powerful channels for transmitting information in text, images, video, and audio, making digital knowledge vast and accessible but relatively diffuse.

Organizing digital information and extracting valuable knowledge requires appropriate techniques. Therefore, text mining techniques for knowledge discovery represent an essential method for processing and systematizing the enormous amount of information available in the literature, social media, image files, and video and audio records, etc. By using natural and technical language, extracting the context and meanings of information from a textual database about a particular phenomenon or situation is possible. The text mining process occurs through a set of data mining techniques and metrics, machine learning, neural networks, and computational linguistics, among others, all combined with ontology, semantics, and linguistics knowledge. Text mining can be used either as a research method or as an object of study itself.

This Special Issue seeks original, unpublished articles that address recent advances in text mining techniques as well as their applications. Authors are invited to submit manuscripts addressing the development of new text mining techniques, such as algorithms, software, computational routines, metrics, and others, that enable processing information in text, image, video, and audio formats. Applications of text mining techniques in different contexts, showing their potential and practical relevance for advancing science, knowledge discovery, and supporting decision making, are also within the scope of this Special Issue. Studies that show the historical evolution of the development of techniques and applications with an emphasis on state-of-the-art and future perspectives are also welcomed. Technical papers, reviews, surveys, and case studies are encouraged. Topics of interest include but are not limited to the following:

• Development of software for text mining;
• Development of independent or shared routines, algorithms, or programming resources (R, VosViewer, Gephi, Pajek, Python, SAS, WordStat, SPSS, and others);
• Applications of Knowledge Discovery in Text in real-life cases (journalism, advertisement, merchandising, marketing, social media, policy and politics, sociology, environment, agricultural sciences, biology, medicine, psychology, information science, management, engineering, and technology, etc.);
• Text mining techniques and applications in knowledge discovery in image-to-text, video-to-text, and audio-to-text;
• Natural language processing—NLP;
• Content analysis automation;
• Emotion and sentiment analysis;
• Machine learning and learning algorithm in continuous text mining process;
• Artificial intelligence and computational linguistics;
• Big data, data mining, and text mining;
• Neural networks;
• Future trends in the development of techniques and applications in text mining;
• Chatbots and Automatic question answering;
• Information retrieval and extraction;
• Ontologies and Knowledge Representation.

You may choose our Joint Special Issue in Future Internet.

Dr. Edson Talamini
Dr. Letícia De Oliveira
Dr. Filipe Portela
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Data is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• text mining
• knowledge discovery in text
• content analysis
• text analysis
• big data
• artificial intelligence
• information retrieval
• audio-to-text mining
• video-to-text mining
• image-to-text mining
• algorithms
• software
• applications