Iramuteq: Difference between revisions

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'''Input documents'''
'''Input documents'''
* This software allows to analyse documents that are segemented into chunks
'''Installation under Ubuntu 14 (Trusty)
* It worked
* Get the deb file
sudo dpkg -i iramuteq_0.6-alpha3_all.deb
# repaire something with python
apt-get -f install


Input documents are plain text files that containing simple markup that identifes variables and topics (see [http://www.iramuteq.org/documentation/formatage-des-corpus-texte  Formatage des corpus texte]. This allows to distinguish between:
Input documents are plain text files that containing simple markup that identifes variables and topics (see [http://www.iramuteq.org/documentation/formatage-des-corpus-texte  Formatage des corpus texte]. This allows to distinguish between:

Revision as of 18:24, 21 October 2014

Iramuteq-logo.png


IRaMuTeQ 0.6 alpha 3 (2014/10/19)

No image.png

Developed by: Pierre Ratinaud, LERASS
License:
Web page : Tool homepage
Tool type : Application software

Tool.png

The last edition of this page was on: 2014/10/21

The Completion level of this page is : Low


SHORT DESCRIPTION

[[has description::IRaMuTeQ stands for "Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires", in English, "interface of R for multi-dimensional text and questionnaire analysis".

Iramutec is built on top of R]]


TOOL CHARACTERISTICS

Usability

Authors of this page consider that this tool is '.

Tool orientation

This tool is designed for general purpose analysis.

Data mining type

This tool is made for Text mining.

Manipulation type

This tool is designed for Data extraction, Data transformation, Data analysis, Data visualisation.

IMPORT FORMAT : TXT

EXPORT FORMAT :


Tool objective(s) in the field of Learning Sciences

Analysis & Visualisation of data
Predicting student performance
Student modelling
Social Network Analysis (SNA)
Constructing courseware

Providing feedback for supporting instructors:
Recommendations for students
Grouping students:
Developing concept maps:
Planning/scheduling/monitoring
Experimentation/observation

Tool can perform:

  • Data extraction of type:
  • Transformation of type:
  • Data analysis of type:
  • Data visualisation of type: (These visualisations can be interactive and updated in "real time")



ABOUT USERS

Tool is suitable for:

Students/Learners/Consumers
Teachers/Tutors/Managers
Researchers
Developers/Designers
Organisations/Institutions/Firms
Others

Required skills:

STATISTICS: Medium

PROGRAMMING: Medium

SYSTEM ADMINISTRATION: Medium

DATA MINING MODELS: Medium



FREE TEXT


Tool version : IRaMuTeQ 0.6 alpha 3 2014/10/19
(blank line)

Developed by : Pierre Ratinaud, LERASS
(blank line)
Tool Web page : http://www.iramuteq.org/
(blank line)
Tool type : Application software
(blank line)

No image.png

SHORT DESCRIPTION


IRaMuTeQ stands for "Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires", in English, "interface of R for multi-dimensional text and questionnaire analysis".

Iramutec is built on top of R

TOOL CHARACTERISTICS


Tool orientation Data mining type Usability
This tool is designed for general purpose analysis. This tool is designed for Text mining. Authors of this page consider that this tool is .
Data import format Data export format
TXT. .
Tool objective(s) in the field of Learning Sciences

☑ Analysis & Visualisation of data
☑ Predicting student performance
☑ Student modelling
☑ Social Network Analysis (SNA)
☑ Constructing courseware

☑ Providing feedback for supporting instructors:
☑ Recommendations for students
☑ Grouping students:
☑ Developing concept maps:
☑ Planning/scheduling/monitoring
Experimentation/observation

Can perform data extraction of type:

Can perform data transformation of type:

Can perform data analysis of type:

Can perform data visualisation of type:
(These visualisations can be interactive and updated in "real time")


ABOUT USER


Tool is suitable for:
Students/Learners/Consumers:☑ Teachers/Tutors/Managers:☑ Researchers:☑ Organisations/Institutions/Firms:☑ Others:☑
Required skills:
Statistics: MEDIUM Programming: MEDIUM System administration: MEDIUM Data mining models: MEDIUM

OTHER TOOL INFORMATION


No screenshot.jpg
Iramuteq-logo.png
IRaMuTeQ
Pierre Ratinaud, LERASS
2014/10/19
0.6 alpha 3
http://www.iramuteq.org/
[[has description::IRaMuTeQ stands for "Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires", in English, "interface of R for multi-dimensional text and questionnaire analysis".

Iramutec is built on top of R]]

General analysis
Researchers
Medium
Medium
Medium
Medium
Application software
Text mining
Data extraction, Data transformation, Data analysis, Data visualisation
TXT
Low

Links

Input documents

  • This software allows to analyse documents that are segemented into chunks

Installation under Ubuntu 14 (Trusty)

  • It worked
  • Get the deb file
sudo dpkg -i iramuteq_0.6-alpha3_all.deb
  1. repaire something with python
apt-get -f install


Input documents are plain text files that containing simple markup that identifes variables and topics (see Formatage des corpus texte. This allows to distinguish between:

  • A text
  • A text segment
  • A combination of text segments

Exemples d'utilisation

  • Marty E., Marchand P., Ratinaud P., 2013. Les médias et l’opinion: éléments théoriques et méthodologiques pour une analyse du débat sur l’identité nationale. Bulletin de méthodologie sociologique, vol. 117, n°1, p. 46‑60.
  • Ratinaud P. et Marchand P. (2012). Application de la méthode ALCESTE à de “gros” corpus et stabilité des “mondes lexicaux”: analyse du “CableGate” avec IRaMuTeQ. In Actes des 11eme Journées internationales d’Analyse statistique des Données Textuelles (pp. 835–844). Presented at the 11eme Journées internationales d’Analyse statistique des Données Textuelles. JADT 2012, Liège, Belgique. Retrieved from http://lexicometrica.univ-paris3.fr/jadt/jadt2012/tocJADT2012.htm

Théorie

  • Reinert M. (1983). Une méthode de classification descendante hiérarchique : application à l'analyse lexicale par contexte, Les cahiers de l'analyse des données, Vol VIII, n° 2, p 187-198.