Filling gaps in early word learning

Years of research has shown that children do not learn words at random, but in distinct patterns. Why do we observe the patterns that we do? By using network science and investigating the words that children don’t learn, researchers have potentially uncovered a general property of word learning as a process of gap forming and filling

The macroscope : a tool for examining the historical structure of language

The recent rise in digitized historical text has made it possible to quantitatively study our psychological past. This involves understanding changes in what words meant, how words were used, and how these changes may have responded to changes in the environment, such as in healthcare, wealth disparity, and war. Here we make available a tool, the Macroscope, for studying historical changes in language over the last two centuries. The Macroscope uses over 155 billion words of historical text, which will grow as we include new historical corpora, and derives word properties from frequency-of-usage and co-occurrence patterns over time. Using co-occurrence patterns, the Macroscope can track changes in semantics, allowing researchers to identify semantically stable and unstable words in historical text and providing quantitative information about changes in a word’s valence, arousal, and concreteness, as well as information about new properties, such as semantic drift. The Macroscope provides information about both the local and global properties of words, as well as information about how these properties change over time, allowing researchers to visualize and download data in order to make inferences about historical psychology. Although quantitative historical psychology represents a largely new field of study, we see this work as complementing a wealth of other historical investigations, offering new insights and new approaches to understanding existing theory. The Macroscope is avail- able online at http://www.macroscope.tech

Profiling commenters on mental health-related online forums : a methodological example focusing on eating disorder-related commenters

Background Understanding the characteristics of commenters on mental health-related online forums is vital for the development of effective psychological interventions in these communities. The way in which commenters interact can enhance our understanding of their characteristics. Objective Using eating disorder-related (EDR) forums as an example, this study details a methodology that aimed to determine subtypes of mental health-related forums, and profile their commenters based on the other forums to which they contributed. Methods The researchers identified all public EDR-forums (with ≥500 contributing commenters between March 2017 and February 2018) on a large online discussion platform (Reddit). A mixed-methods approach comprising network analysis with community-detection, text-mining and manual review identified subtypes of EDR-forums. For each subtype, another network analysis with community-detection was conducted using the EDR-forum commenter-overlap between 50 forums on which the commenters also commented. The topics of forums in each detected community were then manually reviewed to identify the shared interests of each subtype of EDR-forum commenters. Results Six subtypes of EDR-forums were identified, to which 14024 commenters had contributed. The results focus on two subtypes – pro-eating disorder, and thinspiration – and communities of commenters within both subtypes. Within the pro-eating disorder subtype, three communities of commenters were detected that related to the body and eating, mental health, and women, appearance and mixed topics. Regarding the thinspiration group, 78% of commenters had also commented on pornographic forums, and 17% had contributed to pro-eating disorder forums. Conclusions The article exemplifies a methodology that provides insight into subtypes of mental health-related forums, and the characteristics of their commenters. The findings have implications for future research, and online psychological interventions. With the publicly available data and code provided, researchers can easily reproduce the analyses, or utilise the methodology to investigate other mental health-related forums

Investigating the effect of distance entropy on semantic priming

Recent studies have found that people are sensitive to the large-scale network structure of semantic free associations. The current work aims to conduct a stronger test of people’s sensitivity to structural nuances within the semantic network by going beyond measurements of path lengths between word pairs (e.g., Kumar et al., 2019). Here we examine the influence of distance entropy on semantic priming. Distance entropy is the entropy of the shortest paths from a target word to all other words in the network. Simulations suggested that nodes with lower distance entropy (i.e., many shortest paths of similar lengths) led to more “democratic” spread of activation overall—with higher median and less variable activation levels among nodes—and hence should be more “effective” primes. However, analyses of Semantic Priming Project data were not conclusive and targeted experiments are needed to further examine the effect of distance entropy on semantic priming

Evidence of community structure in phonological networks of various languages

Thousands of phonological word-forms known to a speaker can be organized as a lexical network using the tools of network science. In these networks, nodes represent words and edges are placed between phonological neighbors. Previous work has shown that phonological networks of various languages have similar macro-level network properties. The present study investigated if phonological networks of different languages also have similar meso-level properties, specifically, the presence of robust community structure. Community detection analyses conducted on English, French, German, Dutch, and Spanish networks indicate that all networks showed strong evidence of community structure - meso-level clustering of word-forms whereby larger communities tended to contain shorter, frequent words with many phonological neighbors. Words of the same community tended to share similar phonotactic structures. Results suggest that the organization of phonological word-forms in language are governed by similar principles that could have important implications for lexical processing

Using complex networks to understand the mental lexicon

Network science is an emerging discipline drawing from sociology, computer science, physics and a number of other fields to examine complex systems in economical, biological, social, and technological domains. To examine these complex systems, nodes are used to represent individual entities, and links are used to represent relationships between entities, forming a web-like structure, or network, of the entire system. The structure that emerges in these complex networks influences the dynamics of that system. We provide a short review of how this mathematical approach has been used to examine the structure found in the phonological lexicon, and of how subsequent psycholinguistic investigations demonstrate that several of the structural characteristics of the phonological network influence various language-related processes, including word retrieval during the recognition and production of spoken words, recovery from instances of failed lexical retrieval, and the acquisition of word-forms. This approach allows researchers to examine the lexicon at the micro-, meso-, and macro-levels, holding much promise for increasing our understanding of language-related processes and representations.