Abstract-This paper presents the design and performance analysis of an Improved Differential Chaos Shift Keying (I-DCSK) system. Instead of sending reference and data carrier signals in two time slots as in conventional DCSK scheme, in the improved design, a time reversal operation is used to generate an orthogonal reference signal to the data carrier signal and then sum up these two sequences into one time slot, prior to transmission. This operation reduces the bit duration to half, which doubles data rate and enhances spectral efficiency. At the receiver, the received signal is correlated to its time reversed replica and is summed over the bit duration. The new system design proposed in this work replaces the delay circuit used in conventional DCSK systems by time reversal operations. Moreover, the theoretical bit error rate expressions for AWGN and multipath fading channels are analytically studied and derived. The proposed I-DCSK system is compared to the conventional DCSK and Quadrature Chaos Shift Keying (QCSK) schemes. Finally, to validate accuracy, simulation results are compared to relevant theoretical expressions.

With the ubiquity of computer-mediated communication, it is becoming increasingly difficult to choose which medium or content to employ in gratifying whatever use or need people may seek at each point in time. Empirical results in 2012 from questionnaires administered among 289 college students ranging in age from 18 to 28 years show that college students use Social Media Network Sites (SMNSs) for so many reasons. These include keeping in touch with friends (98.9%), sharing photos (81.7%), keeping in touch with family (79.3%), and entertainment (70.9%), among others. Facebook emerged as the preferred SMN site followed by Twitter, while LinkedIn was the least popular site among this group. While some participants still maintain their MySpace account, they depicted this site as archaic and a rarely visited site. Overall, ease of use and potential for eclectic tasks are qualities that garnered Facebook most preferred status as a social networking site.

In this paper, we sought to model and characterize hate speech against immigrants on Twitter in Spain around the appearance of the far-right party Vox. More than 240,000 tweets that included the term ‘Vox’ between November 2018 and April 2019 were automatically collected and analyzed. Only 1% of the sample included hate speech expressions. Within this subsample of 1977 messages, we found offenses (56%), incitements to hate (42%), and violent speech (2%). The most frequent terms used were classified into five categories: Spain, Immigration, Government, Islam, and Insults. The most common features were foul language, false or doubtful information, irony, distasteful expressions, humiliation or contempt, physical or psychological threats, and incitement to violence. Using unsupervised topic modeling, we found that the four underlying topics (control of illegal immigration, economic assistance for immigrants, consequences of illegal immigration, and Spain as an arrival point for African immigrants and Islamist terrorism) were similar to those in the discourse of Vox. We conclude that the hate speech against immigrants produced around Vox, and not necessarily by Vox, followed the general patterns of this type of speech detected in previous works, including Islamophobia, offensive language more often than violent language, and the refusal to offer public assistance to these collectives.

Social media services make it possible for an increasing number of people to express their opinion publicly. In this context, large amounts of hateful comments are published daily. The PHARM project aims at monitoring and modeling hate speech against refugees and migrants in Greece, Italy, and Spain. In this direction, a web interface for the creation and the query of a multi-source database containing hate speech-related content is implemented and evaluated. The selected sources include Twitter, YouTube, and Facebook comments and posts, as well as comments and articles from a selected list of websites. The interface allows users to search in the existing database, scrape social media using keywords, annotate records through a dedicated platform and contribute new content to the database. Furthermore, the functionality for hate speech detection and sentiment analysis of texts is provided, making use of novel methods and machine learning models. The interface can be accessed online with a graphical user interface compatible with modern internet browsers. For the evaluation of the interface, a multifactor questionnaire was formulated, targeting to record the users’ opinions about the web interface and the corresponding functionality.

No abstract

This work analyses the denotative and connotative visual framing of migrants and refugees in European media during the migration crisis in Europe in general and in the Mediterranean in particular. The main objective is to identify the differences between Germany, the country that receives the most asylum requests, and other Western Europe countries (Spain, France, Italy and the United Kingdom). The second goal is to detect temporal differences between the first period of the crisis (2013-2014) and the second period (2015-2017), when the conflict worsened. We content analysed a sample of 500 news photographs from 10 media outlets of five European countries. The results indicate that the most predominant visual frame represents migrants and refugees as victims. However, it was also observed that the frames depicting these individuals as a threat to Western societies are more frequent in German media, and also during the second period of the crisis.

Las noticias falsas plantean uno de los principales desafíos del periodismo contemporáneo. El objetivo de esta investigación es conocer si la deontología periodística ofrece una herramienta útil para luchar contra las noticias falsas. Por medio de una encuesta a 383 periodistas españoles, así como cuatro entrevistas en profundidad a expertos del área, se comprobó la gravedad y el corte deontológico del problema de las noticias falsas, pero la ética periodística no fue considerada la medida más efectiva para luchar contra las fake news. También se buscaban posibles diferencias entre las opiniones de periodistas digitales y tradicionales en su aproximación a las noticias falsas y la deontología. Ambos grupos coinciden en responsabilizar del fenómeno a la situación económica del sector y la nueva forma de comunicación (no necesariamente periodística) en la Red, a lo que añaden la formación de los consumidores como una medida eficaz contra las noticias falsas.

High-profile events can trigger expressions of hate speech online, which in turn modifies attitudes and offline behavior towards stigmatized groups. This paper addresses the first path of this process using manual and computational methods to analyze the stream of Twitter messages in Spanish around the boat Aquarius (n = 24,254) before and after the announcement of the Spanish government to welcome the boat in June 2018, a milestone for asylum seekers acceptance in the EU and an event that was highly covered by media. It was observed that most of the messages were related to a few topics and had a generally positive sentiment, although a significant part of messages expressed rejection or hate—often supported by stereotypes and lies—towards refugees and migrants and towards politicians. These expressions grew after the announcement of hosting the boat, although the general sentiment of the messages became more positive. We discuss the theoretical, practical, and methodological implications of the study, and acknowledge limitations referred to the examined timeframe and to the preliminary condition of the conclusions.