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Nvivo 12 + classification sheet + excel free#
Thus, a short 290-word article “Burrell Collection is set free to tour abroad” in The Times is tagged in LexisNexis with the following keywords: culture departments (90%), legislative bodies (90%), legislation (90%), museums & galleries (89%), painting (79%), art collecting (79%), international tourism (78%), regional & local governments (76%), city government (76%), building renovation (74%), cities (71%), and approvals (70%). For example, in the LexisNexis Academic database, one of the world’s largest general news databases, each article is coded with several keywords that indicate topical areas to which the article can be assigned. However, for certain data domains (e.g., maps, images, or documents in databases), as well as for certain data usage purposes, the requirement to describe a set of data by using one-to-one protocol may be overly restrictive. The existing methods of agreement estimation, e.g., Cohen’s kappa for the two coders, require that coders map each unit of content into one and only one category from the pre-established set of categories (one-to-one protocol). The high level of inter-coder agreement provides assurance in the validity of research results, allows division of coding work among multiple coders, and ensures replicability of the study. Thus, the coding procedure is duplicated by independent coders and their coding outcomes are compared, for which various measures of inter-coder agreement exist there measures are often referred to as reliability indices. Consistency of coding is of crucial importance, as it ensures that inferences made from structured data about the phenomenon under study are valid. However, unless computers are used for coding, content analysis employs literary competent coders who classify original data units according to a given category system such a procedure, inevitably, has a subjective component to it. One way to create structured data from unstructured texts is to use content analysis, a research method that provides “the objective, systematic, and quantitative description of any symbolic behavior”. Prior to analysis, such texts need to be subjected to a systematic reduction of the content flow to reformulate them in quantifiable, that is, analyzable terms. Reality manifests itself in various types of symbolic representations, including naturally occurring texts like tweets, travel photos, or online reviews. It is argued that the measure is especially compatible with data from certain domains, when holistic reasoning of human coders is utilized in order to describe the data and access the meaning of communication. Building on the existing approaches to one-to-many coding in geography and biomedicine, such measure, fuzzy kappa, which is an extension of Cohen’s kappa, is proposed. The restriction could be lifted, provided that there is a measure to calculate the inter-coder agreement in the one-to-many protocol. However, in certain data domains (e.g., maps, photographs, databases of texts and images), this requirement seems overly restrictive.
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The existing methods of agreement estimation, e.g., Cohen’s kappa, require that coders place each unit of content into one and only one category (one-to-one coding) from the pre-established set of categories. The inter-coder agreement is estimated by making two or more coders to classify the same data units, with subsequent comparison of their results. Content analysis involves classification of textual, visual, or audio data.