How Combining Terrorism, Muslim, and Refugee Topics Drives Emotional Tone in Online News: A Six-Country Cross-Cultural Sentiment Analysis

This study looks into how the combination of Islam, refugees, and terrorism topics leads to text-internal changes in the emotional tone of news articles and how these vary across countries and media outlets. Using a multilingual human-validated sentiment analysis, we compare fear and pity in more than 560,000 articles from the most important online news sources in six countries (U.S., Australia, Germany, Switzerland, Turkey, and Lebanon). We observe that fear and pity work antagonistically—that is, the more articles in a particular topical category contain fear, the less pity they will feature. The coverage of refugees without mentioning terrorists and Muslims/Islam featured the lowest fear and highest pity levels of all topical categories studied here. However, when refugees were covered in combination with terrorism and/or Islam, fear increased and pity decreased in Christian-majority countries, whereas no such pattern appeared in Muslim-majority countries (Lebanon, Turkey). Variations in emotions are generally driven more by country-level differences than by the political alignment of individual outlets

OSD2F: An Open-Source Data Donation Framework

The digital traces that people leave through their use of various online platforms provide tremendous opportunities for studying human behavior. However, the collection of these data is hampered by legal, ethical, and technical challenges. We present a framework and tool for collecting these data through a data donation platform where consenting participants can securely submit their digital traces. This approach leverages recent developments in data rights that have given people more control over their own data, such as legislation that now mandates companies to make digital trace data available on request in a machine-readable format. By transparently requesting access to specific parts of this data for clearly communicated academic purposes, the data ownership and privacy of participants is respected, and researchers are less dependent on commercial organizations that store this data in proprietary archives. In this paper we outline the general design principles, the current state of the tool, and future development goals

Do Online Trolling Strategies Differ in Political and Interest Forums : Early Results

This study compares the effectiveness of different trolling strategies in two online contexts: politically oriented forums that address issues like global warming, and interest-based forums that deal with peo- ple’s personal interests. Based on previous research, we consider trolling as context-bound and suggest that relevance theory and common ground- ing theory can explain why people may attend and react to certain types of troll posts in one forum, but pay scant attention to them in another. We postulate two hypotheses on how successful (i.e., disrup- tive) trolling varies according to context: that trolls’ messaging strate- gies appear in different frequencies in political and interest forums (H1), and that context-matching strategies also produce longer futile conver- sations (H2). Using Hardaker’s categorization of trolling strategies on a covert–overt continuum, our statistical analysis on a dataset of 49 online conversations verified H1: in political forums covert strategies were more common than overt ones; in interest forums the opposite was the case. Regarding H2 our results were inconclusive. However, the results moti- vate further research on this phenomenon with larger datasets.Peer reviewe

Social Correlates of and Reasons for Primate Meat Consumption in Central Amazonia

Traditionally, humans have consumed nonhuman primates in many places, including throughout the Amazon region. However, primate consumption rates are changing with rising urbanization and market access. We characterize primate consumption in central Amazonia using 192 qualitative interviews with inhabitants in three rural villages and in the city of Tefé. We used a generalized linear model to investigate how individual consumer characteristics, such as age and gender, and livelihoods affected primate consumption. We also used principal coordinate analysis (PCoA), and word clouds and network text analyses, to describe reasons people gave for eating or avoiding primates. Our results show that men were more likely to say that they eat primates than women, and that the probability that a person said that they eat primates correlated positively with the percentage of their life lived in rural areas. People gave sentiment and ethical reasons not to eat primates. Custom influenced whether people said they eat primates both positively and negatively, while taste positively influenced whether people said they eat primates. A preference for other wild meats in rural areas, and for domestic meats in cities negatively influenced whether people said they eat primates. People also cited the perceptions that primates have a human-like appearance and that primate meat is unhealthy as reasons not to eat primates. People in urban areas also cited conservation attitudes as reasons for not eating primates. Our findings provide an understanding of factors influencing primate consumption in our study area and will be useful for designing tailored conservation initiatives by reducing hunting pressure on primates in rural settings and increasing the effectiveness of outreach campaigns in urban centers

Gatekeeping in the Digital Age

Kleinnijenhuis, J. [Promotor]Atteveldt, W.H. van [Copromotor]Ruigrok, N. [Copromotor

The semantic mapping of words and co-words in contexts

Meaning can be generated when information is related at a systemic level. Such a system can be an observer, but also a discourse, for example, operationalized as a set of documents. The measurement of semantics as similarity in patterns (correlations) and latent variables (factor analysis) has been enhanced by computer techniques and the use of statistics; for example, in "Latent Semantic Analysis". This communication provides an introduction, an example, pointers to relevant software, and summarizes the choices that can be made by the analyst. Visualization ("semantic mapping") is thus made more accessible