What is she best known for?
The fields of study she is best known for:
- Linguistics
- Grammar
- Artificial intelligence
Her scientific interests lie mostly in Linguistics, Language acquisition, Semantics, Meaning and Comprehension.
Her studies in Linguistics integrate themes in fields like Word, Transformational leadership and Psycholinguistics.
Her studies deal with areas such as Social relation, Vocabulary development, Preschool child and Nonverbal communication as well as Language acquisition.
Eve V. Clark has included themes like Pragmatics, Meaning, Theoretical linguistics and First language in her Semantics study.
The concepts of her Meaning study are interwoven with issues in Cognitive development, Word and Order of acquisition.
In her research, Language development is intimately related to Category structure, which falls under the overarching field of Noun.
Her most cited work include:
- Psychology and language : an introduction to psycholinguistics (738 citations)
- The lexicon in acquisition (704 citations)
- WHAT'S IN A WORD? ON THE CHILD'S ACQUISITION OF SEMANTICS IN HIS FIRST LANGUAGE (641 citations)
What are the main themes of her work throughout her whole career to date?
Her primary areas of investigation include Linguistics, Language acquisition, Noun, Comprehension and Conversation.
Her Linguistics study combines topics in areas such as Psycholinguistics and Meaning.
Her research in Psycholinguistics focuses on subjects like Cognitive science, which are connected to Vocabulary.
Her study on Language acquisition also encompasses disciplines like
- Semantics that intertwine with fields like Language development,
- Cognitive development most often made with reference to Cognitive psychology.
The study incorporates disciplines such as Interpersonal communication and Repetition in addition to Conversation.
In her work, Universal Networking Language is strongly intertwined with Second-language acquisition, which is a subfield of Developmental linguistics.
She most often published in these fields:
- Linguistics (74.82%)
- Language acquisition (30.94%)
- Noun (10.07%)
What were the highlights of her more recent work (between 2008-2020)?
- Linguistics (74.82%)
- Language acquisition (30.94%)
- Conversation (10.07%)
In recent papers she was focusing on the following fields of study:
Her primary scientific interests are in Linguistics, Language acquisition, Conversation, First language and Gesture.
Verb, Pragmatics, Utterance, Vocabulary and Context are the primary areas of interest in her Linguistics study.
Her Language acquisition study incorporates themes from Interpersonal communication, Communication, Comprehension and Variation.
Her Conversation research includes themes of Cooperative principle, Part of speech, Semantic domain, Lexical acquisition and Syntax.
The First language study combines topics in areas such as Space and Language community.
Her Gesture research incorporates themes from Noun, Word and Word use.
Between 2008 and 2020, her most popular works were:
- Why Brush Your Teeth Is Better Than Teeth – Children's Word Production Is Facilitated in Familiar Sentence-Frames (77 citations)
- Using speech and gesture to introduce new objects to young children (67 citations)
- Adult offer, word-class, and child uptake in early lexical acquisition (42 citations)
In her most recent research, the most cited papers focused on:
- Linguistics
- Grammar
- Artificial intelligence
Her main research concerns Linguistics, Language acquisition, Gesture, Verb and Conversation.
With her scientific publications, her incorporates both Linguistics and Metalinguistics.
The various areas that Eve V. Clark examines in her Language acquisition study include Interpersonal communication, Comprehension and Word formation.
Her Gesture research is multidisciplinary, relying on both Word, Communication and Inflection.
Her Verb research incorporates elements of Class, Construct, Homophony and Meaning.
Her work in Conversation addresses subjects such as Pragmatics, which are connected to disciplines such as Meaning.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
