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The integration of digital technology in modern society has led to an increased importance of the analysis of the digital environment in political elections. The concept of echo chambers and their influence on social networks has received significant attention in recent academic investigations. Echo chambers are commonly referred to as the digital bubble where users participate in a conversation mostly with like-minded others, and it is usually related not only to homophily but can also be directly associated with the effects of social media algorithms. This study examines the Twitter interactions during two Spanish regional elections. Data collection has been performed through Twitter Streaming API, which resulted in a total dataset of 5.5 million tweets. The study analyzes how the political communities interact inside and between them. Also, we replicate this analysis by grouping the political communities by two main affinity blocks (left-right) to evaluate if the effects of homophily are even higher under this hypothesis. Finally, the text of the tweets was analyzed to reinforce the community-interaction analysis and to conduct a sentiment analysis of the interactions. The research results indicate that within each political party community, interactions predominantly occur among individuals who hold similar political views, leading to the creation of echo chambers. These echo chambers become even more powerful when parties are unified into political affinity blocks, with over 97% of interactions occurring within each left-right block. This study aims to contribute to the ongoing academic debate by providing relevant data and reinforcing aspects studied by previous researchers.

The integration of digital technology in modern society has led to an increased importance of the analysis of the digital environment in political elections. The concept of echo chambers and their influence on social networks has received significant attention in recent academic investigations. Echo chambers are commonly referred to as the digital bubble where users participate in a conversation mostly with like-minded others, and it is usually related not only to homophily but can also be directly associated with the effects of social media algorithms. This study examines the Twitter interactions during two Spanish regional elections. Data collection has been performed through Twitter Streaming API, which resulted in a total dataset of 5.5 million tweets. The study analyzes how the political communities interact inside and between them. Also, we replicate this analysis by grouping the political communities by two main affinity blocks (leftright) to evaluate if the effects of homophily are even higher under this hypothesis. Finally, the text of the tweets was analyzed to reinforce the community-interaction analysis and to conduct a sentiment analysis of the interactions. The research re-sults indicate that within each political party community, interactions predominantly occur among individuals who hold similar political views, leading to the creation of echo chambers. These echo chambers become even more powerful when parties are unified into political affinity blocks, with over 97% of interactions occurring within each left-right block. This study aims to contribute to the ongoing academic debate by providing relevant data and reinforcing aspects studied by previous researchers. [ABSTRACT FROM AUTHOR]

Summary: Since digital artworks are indeed digital content, they face the inherent problem digital content has: the link between content and its original author is very difficult to keep. Additionally, retaining control over digital copies of the content is also a challenging task. Digital coins have solved this very same problem through cryptocurrencies (for instance, Bitcoin) and have opened the door to apply the same techniques to other similar scenarios where ownership of digital assets needs to be preserved. In this paper, we propose BArt, a transparent and distributed mechanism for artists to commercialize their digital artwork, keeping control of the copies, monetizing its usage, and maintaining ownership. BArt allows artists to publicly register their work in the Bitcoin blockchain and sell usage rights in exchange for bitcoins. Buyers are allowed to exert the acquired rights. Proper behavior from all parties is enforced by the system with cryptography and economic incentives. [ABSTRACT FROM AUTHOR]

This paper presents a classifier architecture that is able to deal with classification of interlinked entities when the only information available is the existing relationships between these entities, i.e. no semantic content is known for either the entities or their relationships. After proposing a classifier to deal with this problem, we provide extensive experimental evaluation showing that our proposed method is sound and that it is able to achieve high accuracy, in most cases much higher than other already existing algorithms configured to tackle this very same problem. The contributions of this paper are twofold: first, it presents a classifier for interlinked entities that outperforms most of the existing algorithms when the only information available is the relationships between these entities; second, it reveals the power of using label independent (LI) features extracted from network structural properties in the bootstrapping phases of relational classification. [ABSTRACT FROM AUTHOR]

Web crawlers are complex applications that explore the Web for different purposes. Web crawlers can be configured to crawl online social networks (OSNs) to obtain relevant data about their global structure. Before a web crawler can be launched to explore the Web, a large amount of settings have to be configured. These settings define the crawler's behavior and they have a big impact on the collected data. Both the amount of collected data and the quality of the information that it contains are affected by the crawler settings and, therefore, by properly configuring these web crawler settings we can target specific goals to achieve with our crawl. In this paper, we review the configuration choices that an attacker who wants to obtain information from an OSN by crawling it has to make to conduct his attack. We analyze different scheduler algorithms for web crawlers and evaluate their performance in terms of how useful they are to pursue a set of different adversary goals. [ABSTRACT FROM AUTHOR]