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EN
Organizing principles of the mental lexicon are a long studied and discussed research area in linguistics. On the one hand, the paper intends to analyse and to compare traditional methods used by psycholinguists and cognitive linguists for describing the mental lexicon. In this section the approaches using the analogue of a network for the organisation of the mental lexicon are mentioned in detail. On the other hand, present paper also shows, how new methods borrowed from the now emerging field of network research can be used for a better understanding of the mental lexicon.
DE
Vorliegender Beitrag versteht sich als explorativer Ansatz zum interdisziplinären Forschungsfeld der Markenforschung: es soll gezeigt werden, wie die aus der Psycholinguistik bekannte Methode der Wortassoziationsforschung dazu beitragen kann, die kognitive Repräsentation der Marken besser verstehen zu können. Zu diesem Ziel wurden zu 300 deutschen, ungarischen und internationalen Marken die häufigsten Assoziationen abgefragt und die Assoziationen miteinander verglichen. Im Beitrag werden die ersten Ergebnisse und Analysen gezeigt und Unterschiede in den kognitiven Markenrepräsentationen der deutschen und ungarischen Versuchspersonen eruiert – mit besonderem Hinblick auf ausgewählte Automarken und Lebensmittelmarken.
EN
The present paper explores how the psycholinguistic method of word association research can be used in the interdisciplinary field of brand research for a better understanding of the mental representation of brands. Brand associations for 300 German, Hungarian and international brands were collected from Hungarian and German students to show the differences and similarities in the mental representation of brands. The paper shows the first results and analyses with a particular focus on automobile and food brands.
EN
In the new era of information and communication technology, the representation of information is of increasing importance. Knowing how words are connected to each other in the mind and what processes facilitate the creation of connections could result in better optimized applications, e.g. in computer aided education or in search engines. This paper models the growth process of a word association database with an algorithm. We present the network structure of word associations for an agglutinative language and compare it with the network of English word associations. Using the real-world data so obtained, we create a model that reproduces the main features of the observed growth process and show the evolution of the network. The model describes the growth of the word association data as a mixture of a topic based process and a random process. The model makes it possible to gain insight into the overall processes which are responsible for creating an interconnected mental lexicon.
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