``Don't discuss'': Investigating Semantic and Argumentative Features for Supervised Propagandist Message Detection and Classification

One of the mechanisms through which disinformation is spreading online, in particular through social media, is by employing propaganda techniques. These include specific rhetorical and psychological strategies, ranging from leveraging on emotions to exploiting logical fallacies. In this paper, our goal is to push forward research on propaganda detection based on text analysis, given the crucial role these methods may play to address this main societal issue. More precisely, we propose a supervised approach to classify textual snippets both as propaganda messages and according to the precise applied propaganda technique, as well as a detailed linguistic analysis of the features characterising propaganda information in text (e.g., semantic, sentiment and argumentation features). Extensive experiments conducted on two available propagandist resources (i.e., NLP4IF'19 and SemEval'20-Task 11 datasets) show that the proposed approach, leveraging different language models and the investigated linguistic features, achieves very promising results on propaganda classification, both at sentence- and at fragment-level.

CommitBERT: Commit Message Generation Using Pre-Trained Programming Language Model

Commit message is a document that summarizes source code changes in natural language. A good commit message clearly shows the source code changes, so this enhances collaboration between developers. Therefore, our work is to develop a model that automatically writes the commit message. To this end, we release 345K datasets consisting of code modification and commit messages in six programming languages (Python, PHP, Go, Java, JavaScript, and Ruby). Similar to the neural machine translation (NMT) model, using our dataset, we feed the code modification to the encoder input and the commit message to the decoder input and measure the result of the generated commit message with BLEU-4. Also, we propose the following two training methods to improve the result of generating the commit message: (1) A method of preprocessing the input to feed the code modification to the encoder input. (2) A method that uses an initial weight suitable for the code domain to reduce the gap in contextual representation between programming language (PL) and natural language (NL).

The Human right to confidentiality of postal correspondence and contacts wired and wireless

Approved a Syrian legislator confidentiality of postal correspondence and telecommunications protect the right constitutional and legal for a person, expresses hereby expressly intention to protect his privacy and his secrets expressing his thoughts and opinions, freedom of thinking, communication and exchange of information, but this does not mean that the freedom of the individual in this secret absolute, but are given by some of the restrictions that allow eavesdropping and compromised in order to achieve justice and the interests of society according to the decision of the Syrian legislature in the Code of Criminal Procedure, as Syrian legislator intervened to devote their protection sometimes in the face of ordinary people, or in the face of tempted to disclosure of public officials at other times, but Syrian legislator omitted to protect the means to contact an updated e-mail correspondence, which is exposed through it for many attacks, which require effective protection avoiding the legislative vacuum.