Publication patterns in developmental psychology: Trends and social networks

Abstract

Interest in publication patterns has been steady. Journals have instituted policies in an effort to curb bias and provide globally representative research. This study aimed to examine if publication patterns were present in two developmental psychology journals. It also explored the social networks of prominent authors and the prevalence of informal author-editor relationships, searching for any potential power groups. Data were taken from empirical articles published between 2005 and 2014 in Child Development (CD) and The International Journal of Early Childhood (IJEC) data points were geographical authorship affiliation, informal author relationships as established by co-publishing, and connections to journal editors via identical affiliation. Results confirmed the previously established North American dominance in published research. In CD a strongly interlinked social network was identified between authors over the 10 years, with 15 chief influentialists binding groups of authors together. Results suggest that patterns are still present in published research in the realm of developmental psychology. To conclude, the potential implications of these patterns within developmental psychology are presented.

Hidden participants and unheard voices? A systematic review of gender, age, and other influences on local and traditional knowledge research in the North

“…A third limitation is our focus on only English-language literature, which necessarily excludes papers written in Russian and French, and, as such, may contribute to the geographic distribution of studies noted above. We note that language barriers have been a challenge for collaboration in Arctic studies, and this can reinforce the issue of invisible colleges discussed below (Dobermann and Hamilton 2017). Cross-cultural collaboration in Arctic research that addresses the language barrier would be extremely valuable.…”

“…It is essential that researchers be self-aware of the possible influence that these networks, regardless of how they form, can have on how knowledge is generated: invisible colleges can have a sizable impact on accepted methodology and scholastic achievements in an area of research, as they inflate citations of college members relative to non-college members, and in so doing influence research patterns, for example, acceptable methodologies and analytical frameworks. In psychological research, for example, invisible colleges have been shown to keep new researchers out of established fields of specialization, because of "in-group favoritism" and by amplifying linguistic and cultural barriers (Dobermann and Hamilton 2017). We likewise know from Indigenous scholarship that invisible colleges can create a "politics of citation" that perpetuate structural inequities in academia that limit the inclusion of marginalized voices (Todd 2016).…”

“…LTK research is a work in progress, and we are confident in saying that this body of research exhibits an earnest desire on the part of the authors to use research to empower local communities facing climate change. Rather, the key people in these networks are uniquely situated to make this area of scholarship more inclusive and create positive change on the various issues noted above (Dobermann and Hamilton 2017). To continue to move the field forward, leaders in this research should continually seek out new colleagues with new perspectives and approaches, the isolates in Fig.…”

Analysis of The Development Trend of Sports Research in China and Taiwan Using Natural Language Processing

“…The process of this study was based on the concepts of text mining and NLP. For more, please refer to [5][6][7][14][15][16]18,[27][28][29][30]. In the SCI (science citation index) and SSCI (social science citation index) articles of [31], through the steps of text retrieval, word segmentation, word cloud analysis, TF-IDF analysis, co-word analysis, network analysis, trend analysis, etc., the text data of the two regions are excavated for comparison and analysis of their similarities and differences.…”

“…In order to make up for the shortcomings of the content analysis method, such as being time-consuming, laborious, and not objective, this study proposes a program for analyzing and processing text data in sports-related fields based on the concept of NLP, which is different from the traditional content analysis method, with a faster automative analytical process and the ability to systematically extract and analyze the importance and relevance of keywords in abstract content [5,13]. It integrates the methods of word segmentation, word cloud analysis, TF-IDF (term frequency-inverse document frequency) analysis, and co-word analysis, and then applies visual network diagramics drawing technology [14][15][16][17][18] to present the distribution of core keywords and their network relationships in sports research abstracts from China and Taiwan (a total of 3,283 articles). This reveals possible hidden knowledge structures and provides an important reference for evaluating future development trends in the two regions.…”