João Gonçalves

Num contexto em que a comunicação e os media desempenham um papel central na construção das sociedades contemporâneas, a investigação científica é um recurso indispensável para compreendermos os fenómenos, práticas e processos comunicacionais. Este Manual de Métodos de Investigação em Comunicação oferece uma abordagem abrangente sobre os principais paradigmas, métodos e técnicas utilizados nas Ciências da Comunicação, articulando reflexão epistemológica, rigor metodológico e aplicação prática. Concebido para apoiar estudantes, investigadores e docentes, o livro percorre as diferentes etapas do processo de investigação, desde a formulação de problemas e questões de pesquisa até à recolha, análise e interpretação de dados. Ao longo de quinze capítulos, apresenta orientações metodológicas, exemplos práticos e exercícios que permitem consolidar conhecimentos e desenvolver competências essenciais para a realização de investigação científica de qualidade. Assumindo que os métodos de investigação são mais do que um conjunto de procedimentos técnicos, esta obra propõe uma compreensão crítica e reflexiva da produção do conhecimento, valorizando a relação entre teoria, metodologia e contexto. Reunindo contributos de especialistas de diferentes áreas e posicionamentos metodológicos, é um recurso para quem pretende iniciar-se na investigação em Comunicação ou aprofundar a sua prática. Mais do que um manual, esta obra é um convite à exploração crítica dos caminhos da investigação e ao fortalecimento da cultura científica no espaço académico lusófono.

We analyzed the social media posts of top 20 European and US companies for their Diversity related content before (2024) and after (2025) the election of Donald Trump. We find that there was a decline in diversity related content in 2025 both in the US and in Europe, with the biggest drop being registered in the US. From all social media content, 6,7% of posts by US based companies in 2024 included diversity related topics, while in 2025 only 1,3% were about diversity. For European companies, the scenario is similar. In 2024, 12,6% of social media posts by European companies touch upon diversity content which dropped to 7,0% in the same period of 2025. In general, European companies posted more on diversity than American companies both in 2024 and in 2025. These results show us that while the drop in diversity related talk by corporations was more accentuated in the US, other geographies seem to also replicate the trend.

Machine learning-based artificial intelligence (AI) chatbots are increasingly used to promote health and encourage individuals to adopt healthier behaviors. Chatbots driven by generative AI (genAI) simulate human interactions through text or voice to generate personalized content with guidance on topics such as smoking cessation, nutrition, managing stress, and sleep improvement. The use of AI chatbots for health promotion and wellness has been growing since 2023. While empirical evidence suggests their effectiveness in supporting behavioral change and mental health, the legal, ethical, and societal implications remains largely unexplored. This article presents a qualitative case study of S.A.R.A.H. (Smart AI Resource Assistant for Health), a genAI chatbot developed by the World Health Organization (WHO), analyzed against the six ethical principles outlined in the WHO's 2021 Guidance on Ethics and Governance of AI for Health. We also gathered exploratory insights from adolescent focus groups. These findings are descriptive and not based on formal thematic analysis. Drawing on this analysis, we identify key gaps between high-level ethical principles and practice and offer policy recommendations to guide responsible use of AI chatbots for health promotion.

Algorithmic moderation is often presented as the only solution to the scale of harmful and hateful content disseminated online. This chapter questions this assertion by contextualizing the need and scope of algorithmic moderation based on normative considerations, followed by a set of critical issues to be approached in the study of algorithmic moderation, such as the systemic biases that underlie technical approaches to algorithmic performance and asymmetries in access to AI data and knowledge. We then illustrate these issues with the specific case of hate speech and finally consider some of the differences in how human and algorithmic moderators are perceived. This chapter is structured as a starting point for scholars who wish to venture into the study of algorithmic moderation, its antecedents, and consequences.

Using data from a conjoint experiment in three countries (Brazil, n = 2038; Germany, n = 2012, and the United States, n = 2005), this study demonstrates that journalistic transparency can cue trust at the level of the entire news outlet—or domain level—using a Google Knowledge Panel that comes up when people search for a news outlet. In Brazil and the United States, two pieces of information in a Knowledge Panel provided the strongest heuristics that a news outlet was trustworthy: a description of the news outlet and a description of other sites accessed by people who frequent that news outlet’s website. In Germany, information about journalists and the description of the news outlet were the strongest cues. Results offer insights into how people heuristically process online news and are discussed in relation to the heuristic-systematic model of information processing.

Most scholars focus on the prevalence and democratic effects of (partisan) news exposure. This focus misses large parts of online activities of a majority of politically disinterested citizens. Although political content also appears outside of news outlets and may profoundly shape public opinion, its prevalence and effects are under-studied at scale. This project combines three-wave panel survey data from three countries (total N = 6,892) with online behavioral data from the same participants (119.7M visits). We create a multi-lingual classifier to identify political content both in news and outside (e.g. in shopping or entertainment sites). We find that news consumption is infrequent: just 3.4% of participants’ online browsing comprised visits to news sites. Only between 14% (NL) and 36% (US) of these visits were to hard news. The overwhelming majority of participants' visits were to non-news sites. Although only 1.6% of those visits related to politics, in absolute terms, citizens encounter politics more frequently outside of news than within news. Out of every 10 visits to political content, 3 come from news and 7 from non-news sites. Furthermore, non-news exposure to political content had the same – and in some cases stronger - associations with key democratic attitudes and behaviors as news exposure. These findings offer a comprehensive analysis of the online political (not solely news) ecosystem and demonstrate the importance of assessing the prevalence and effects of political content in non-news sources.