Content analysis: Difference between revisions

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* [http://gate.ac.uk/ GATE] is quote an {{quotation|open source software capable of solving almost any text processing problem}}. See the [http://gate.ac.uk/2mins.html 2 Minute Guide]. It can be compared to RapidMiner.
* [http://gate.ac.uk/ GATE] is quote an {{quotation|open source software capable of solving almost any text processing problem}}. See the [http://gate.ac.uk/2mins.html 2 Minute Guide]. It can be compared to RapidMiner.
* [http://www.cs.cmu.edu/~cprose/TagHelper.html TagHelper] is one of more popular tools for analysing texts in education. It also has been integrated into learning systems (Dönmez, 2005; Kumar, 2007). Lightside (below) can be considered a successor.


* [http://lightsidelabs.com/what/research/ Lightside] is a free open source text minin and machine learning tool that provides features to assess student writing. Quote: {{quotation| LightSide began as an open source text mining and machine learning tool. Our core technology is freely available. We offer quick-start tutorials on machine learning for beginners and an introduction to error analysis. The workbench, as well as the core technology for machine learning and feature extraction, was developed under grants from National Science Foundation and the Office of Naval Research, through Carnegie Mellon University’s Language Technologies Institute.}}
* [http://lightsidelabs.com/what/research/ Lightside] is a free open source text minin and machine learning tool that provides features to assess student writing. Quote: {{quotation| LightSide began as an open source text mining and machine learning tool. Our core technology is freely available. We offer quick-start tutorials on machine learning for beginners and an introduction to error analysis. The workbench, as well as the core technology for machine learning and feature extraction, was developed under grants from National Science Foundation and the Office of Naval Research, through Carnegie Mellon University’s Language Technologies Institute.}}

Revision as of 18:08, 7 January 2014

Draft

Definition

Content analysis refers to a family of qualitative data analysis methods or to various forms of quantitative analysis.

“Content analysis (sometimes called textual analysis when dealing exclusively with text) is a standard methodology in the social sciences for studying the content of communication. Earl Babbie defines it as "the study of recorded human communications, such as books, websites, paintings and laws." Harold Lasswell formulated the core questions of content analysis: "Who says what, to whom, why, to what extent and with what effect?." Ole Holsti (1969) offers a broad definition of content analysis as "any technique for making inferences by objectively and systematically identifying specified characteristics of messages."” (Wikipedia, retrieved nov 1 2007)

See also:

This entry should be split into two different articles: qualitative content analysis and machine analysis (e.g. text mining) - Daniel K. Schneider 14:01, 12 March 2012 (CET).

Links

(Semi-) manual qualitative data analysis

Quantitative analysis of large corpus

  • Text mining (German Wikipedia). Better, if you speak German.
  • Text Insight. serves as a research and academic portal for those doing qualitative analysis and text analytics. Main focus of the site is the Leximancer tool However, all researchers, students, academics, and commercial entities are welcome to use this portal and its resources.

Software

See other wiki pages of interest

These pages include specialised technologies

  • latent semantic analysis and indexing, a family of analysis techniques that that assume that a text contains a semantic structure through a kind vector space model and some kind of factor analysis that identifies relationships between terms.

List of tools

(needs completion)

  • Tropes logiciel d'analyse sémantique de textes
  • tOKo is an open source tool for text analysis and browsing a corpus of documents. It implements a wide variety of text analysis and browsing functions in an interactive user interface. It can for instance be used to analyse the exchange of information, for example in a community forum or through a collection of interconnected weblogs.
  • Leximancer, allows to summarize and navigate large text data (e.g. a wiki site) with various visualization tools. (commercial, $750 AUD single license or $150 one-month online)
  • RapidMiner. Quote: “is unquestionably the world-leading open-source system for data mining. It is available as a stand-alone application for data analysis and as a data mining engine for the integration into own products.”. The system is based on the earlier YALE system. Commercial versions of RapidMiner can do more than the free community edition.
  • Weka 3: Data Mining Software in Java is quote: “a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.”
  • GATE is quote an “open source software capable of solving almost any text processing problem”. See the 2 Minute Guide. It can be compared to RapidMiner.
  • TagHelper is one of more popular tools for analysing texts in education. It also has been integrated into learning systems (Dönmez, 2005; Kumar, 2007). Lightside (below) can be considered a successor.
  • Lightside is a free open source text minin and machine learning tool that provides features to assess student writing. Quote: “LightSide began as an open source text mining and machine learning tool. Our core technology is freely available. We offer quick-start tutorials on machine learning for beginners and an introduction to error analysis. The workbench, as well as the core technology for machine learning and feature extraction, was developed under grants from National Science Foundation and the Office of Naval Research, through Carnegie Mellon University’s Language Technologies Institute.”

More should be added here ! In the meantime, see Text Mining at Wikipedia.

Simple word graphics

Bibliography

(to do )

Text and data mining

  • Xiaojun Chen, Yunming Ye, Graham Williams, and Xiaofei Xu, A Survey of Open Source Data Mining Systems. PDF


Analysis of text quality

....

Analysis of on-line interactions

  • De Wever, B., Schellens, T., Valcke, M., and Van Keer, H. 2006. Content analysis schemes to analyze transcripts of online asynchronous discussion groups: a review. Comput. Educ. 46, 1 (Jan. 2006), 6-28. DOI= http://dx.doi.org/10.1016/j.compedu.2005.04.005
  • Pena-Shaff, J. B. and Nicholls, C. 2004. Analyzing student interactions and meaning construction in computer bulletin board discussions. Computers and Education 42, 3 (Apr. 2004), 243-265. DOI= http://dx.doi.org/10.1016/j.compedu.2003.08.003
  • Rourke, L., Anderson, T., Garrison, D. R., & Archer, W. (2001). Methodological Issues in the Content Analysis of Computer Conference Transcripts. International Journal of Artificial Intelligence in Education, 12(1), 8-22. PDF
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