AUSSDA

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AUTNES

Statistik Austria

ASEP

SSÖ-ISSP

GGP

COVID-19 Pandemic

Teaching and Learning

GfK Austria

RECONNECT

Survey Methods: Insights from the Field

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3,011 to 3,020 of 5,984 Results

Replication Data for: Text Message (SMS) Pre-notifications, Invitations and Reminders for Web Surveys Dec 11, 2020 - Survey Methods: Insights from the Field Andreadis, Ioannis, 2020, "Replication Data for: Text Message (SMS) Pre-notifications, Invitations and Reminders for Web Surveys", https://doi.org/10.11587/DX8NNE, AUSSDA, V1 This paper presents the findings derived from a mobile friendly web survey, during which all invitations and reminders were sent as text messages via short message service (SMS) to the mobile telephones of the target group. The web survey under study was conducted for the National Theatre of Northern Greece (NTNG), the largest theatrical organizati...
10667_da_en_v1_0.Rdata Dec 11, 2020 - Replication Data for: Text Message (SMS) Pre-notifications, Invitations and Reminders for Web Surveys Gzip Archive - 24.5 KB - MD5: 40c113ce9d2b95f7942b743f1da113bf DataR Core data file - R format
10667_sx_en_v1_0.R Dec 11, 2020 - Replication Data for: Text Message (SMS) Pre-notifications, Invitations and Reminders for Web Surveys R Syntax - 13.6 KB - MD5: 79be238885f3456aef54585a90ab77bb CodeDocumentation R code for replication
The German Political Sentiment Dictionary (SUF edition) Dec 2, 2020 - AUTNES Haselmayer, Martin; Jenny, Marcelo, 2020, "The German Political Sentiment Dictionary (SUF edition)", https://doi.org/10.11587/7PFLIU, AUSSDA, V1, UNF:6:fddvmzxSkM88VgrqvxOqTg== [fileUNF] Full edition for scientific use. This dataset contains a German-language sentiment dictionary of 5001 negative words and their associated sentiment strength on a five-point-scale from 0 (not negative) to 4 (very strongly negative). The procedure for building the dictionary contains the following steps: (1) Sampling 12713 sentences from Austrian par...
10274_da_de_v1_0.tab Dec 2, 2020 - The German Political Sentiment Dictionary (SUF edition) Tabular Data - 399.2 KB - 8 Variables, 5001 Observations - UNF:6:fddvmzxSkM88VgrqvxOqTg== DataSTATA Core data file - STATA format - 8 Variables, 5001 Observations
10274_mr_en_v1_0.pdf Dec 2, 2020 - The German Political Sentiment Dictionary (SUF edition) Adobe PDF - 62.9 KB - MD5: 050d20c9d45e62745c30f748be8cb9ed DocumentationMethod report Method report
Training Data for German Sentiment Analysis of Political Communication (SUF edition) Nov 26, 2020 - AUTNES Haselmayer, Martin; Jenny, Marcelo, 2020, "Training Data for German Sentiment Analysis of Political Communication (SUF edition)", https://doi.org/10.11587/EOPCOB, AUSSDA, V1, UNF:6:wx/QlNpI73mL4r3N+cNhBg== [fileUNF] Full edition for scientific use. The dataset contains 125871 sentences extracted from Austrian parliamentary debates and party press releases. Press releases were collected under the auspices of the Austrian National Election Study (AUTNES) and cover 6 weeks prior to each national election 1995-2013. Data from parliamentary debates stem from a rand...
10273_da_de_v1_0.tab Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition) Tabular Data - 22.3 MB - 7 Variables, 125871 Observations - UNF:6:IiVRvJlBGz0ZxTi2febxHA== DataSTATA Core data file - STATA format - 7 Variables, 125871 Observations
10273_da_de_v1_0.zsav Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition) Unknown - 8.7 MB - MD5: e3f5c926014383e982a9ec524e04e8cc DataSPSS Core data file - compressed SPSS format - 7 Variables, 125871 Observations
10273_mr_en_v1_0.pdf Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition) Adobe PDF - 84.7 KB - MD5: 956d09f91536890f37733442f4b5a62f DocumentationMethod report Method report

Replication Data for: Text Message (SMS) Pre-notifications, Invitations and Reminders for Web Surveys

Dec 11, 2020 - Survey Methods: Insights from the Field

Andreadis, Ioannis, 2020, "Replication Data for: Text Message (SMS) Pre-notifications, Invitations and Reminders for Web Surveys", https://doi.org/10.11587/DX8NNE, AUSSDA, V1

This paper presents the findings derived from a mobile friendly web survey, during which all invitations and reminders were sent as text messages via short message service (SMS) to the mobile telephones of the target group. The web survey under study was conducted for the National Theatre of Northern Greece (NTNG), the largest theatrical organizati...

10667_da_en_v1_0.Rdata

Dec 11, 2020 - Replication Data for: Text Message (SMS) Pre-notifications, Invitations and Reminders for Web Surveys

Gzip Archive - 24.5 KB -

DataR

Core data file - R format

10667_sx_en_v1_0.R

Dec 11, 2020 - Replication Data for: Text Message (SMS) Pre-notifications, Invitations and Reminders for Web Surveys

R Syntax - 13.6 KB -

CodeDocumentation

R code for replication

The German Political Sentiment Dictionary (SUF edition)

Dec 2, 2020 - AUTNES

Haselmayer, Martin; Jenny, Marcelo, 2020, "The German Political Sentiment Dictionary (SUF edition)", https://doi.org/10.11587/7PFLIU, AUSSDA, V1, UNF:6:fddvmzxSkM88VgrqvxOqTg== [fileUNF]

Full edition for scientific use. This dataset contains a German-language sentiment dictionary of 5001 negative words and their associated sentiment strength on a five-point-scale from 0 (not negative) to 4 (very strongly negative). The procedure for building the dictionary contains the following steps: (1) Sampling 12713 sentences from Austrian par...

10274_da_de_v1_0.tab

Dec 2, 2020 - The German Political Sentiment Dictionary (SUF edition)

Tabular Data - 399.2 KB - 8 Variables, 5001 Observations -

DataSTATA

Core data file - STATA format - 8 Variables, 5001 Observations

10274_mr_en_v1_0.pdf

Dec 2, 2020 - The German Political Sentiment Dictionary (SUF edition)

Adobe PDF - 62.9 KB -

DocumentationMethod report

Method report

Training Data for German Sentiment Analysis of Political Communication (SUF edition)

Nov 26, 2020 - AUTNES

Haselmayer, Martin; Jenny, Marcelo, 2020, "Training Data for German Sentiment Analysis of Political Communication (SUF edition)", https://doi.org/10.11587/EOPCOB, AUSSDA, V1, UNF:6:wx/QlNpI73mL4r3N+cNhBg== [fileUNF]

Full edition for scientific use. The dataset contains 125871 sentences extracted from Austrian parliamentary debates and party press releases. Press releases were collected under the auspices of the Austrian National Election Study (AUTNES) and cover 6 weeks prior to each national election 1995-2013. Data from parliamentary debates stem from a rand...

10273_da_de_v1_0.tab

Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition)

Tabular Data - 22.3 MB - 7 Variables, 125871 Observations -

DataSTATA

Core data file - STATA format - 7 Variables, 125871 Observations

10273_da_de_v1_0.zsav

Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition)

Unknown - 8.7 MB -

DataSPSS

Core data file - compressed SPSS format - 7 Variables, 125871 Observations

10273_mr_en_v1_0.pdf

Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition)