English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Mindset reconstruction maps how individuals structure and perceive knowledge,a map unfolded here by investigating language and its cognitive reflection inthe human mind, i.e. the mental lexicon. Textual forma mentis networks (TFMN)are glass boxes introduced for extracting, representing and understandingmindsets' structure, in Latin "forma mentis", from textual data. Combiningnetwork science, psycholinguistics and Big Data, TFMNs successfully identifiedrelevant concepts, without supervision, in benchmark texts. Once validated,TFMNs were applied to the case study of the gender gap in science, which wasstrongly linked to distorted mindsets by recent studies. Focusing over socialmedia perception and online discourse, this work analysed 10,000 relevanttweets. "Gender" and "gap" elicited a mostly positive perception, with atrustful/joyous emotional profile and semantic associates that: celebratedsuccessful female scientists, related gender gap to wage differences, and hopedfor a future resolution. The perception of "woman" highlighted discussion aboutsexual harassment and stereotype threat (a form of implicit cognitive bias)relative to women in science "sacrificing personal skills for success". Thereconstructed perception of "man" highlighted social users' awareness of themyth of male superiority in science. No anger was detected around "person",suggesting that gap-focused discourse got less tense around genderless terms.No stereotypical perception of "scientist" was identified online, differentlyfrom real-world surveys. The overall analysis identified the online discourseas promoting a mostly stereotype-free, positive/trustful perception of genderdisparity, aware of implicit/explicit biases and projected to closing the gap.TFMNs opened new ways for investigating perceptions in different groups,offering detailed data-informed grounding for policy making.

Text-mining forma mentis networks reconstruct public perception of the STEM gender gap in social media