| Title |
The tool for the automatic analysis of text cohesion (TAACO): Automatic assessment of local, global, and text cohesion
|
|---|---|
| Published in |
Behavior Research Methods, September 2015
|
| DOI | 10.3758/s13428-015-0651-7 |
| Pubmed ID | |
| Authors |
Scott A. Crossley, Kristopher Kyle, Danielle S. McNamara |
| Abstract |
This study introduces the Tool for the Automatic Analysis of Cohesion (TAACO), a freely available text analysis tool that is easy to use, works on most operating systems (Windows, Mac, and Linux), is housed on a user's hard drive (rather than having an Internet interface), allows for the batch processing of text files, and incorporates over 150 classic and recently developed indices related to text cohesion. The study validates TAACO by investigating how its indices related to local, global, and overall text cohesion can predict expert judgments of text coherence and essay quality. The findings of this study provide predictive validation of TAACO and support the notion that expert judgments of text coherence and quality are either negatively correlated or not predicted by local and overall text cohesion indices, but are positively predicted by global indices of cohesion. Combined, these findings provide supporting evidence that coherence for expert raters is a property of global cohesion and not of local cohesion, and that expert ratings of text quality are positively related to global cohesion. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 220 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | <1% |
| Unknown | 219 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 55 | 25% |
| Student > Master | 17 | 8% |
| Student > Bachelor | 17 | 8% |
| Researcher | 16 | 7% |
| Professor | 11 | 5% |
| Other | 36 | 16% |
| Unknown | 68 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Linguistics | 49 | 22% |
| Computer Science | 26 | 12% |
| Social Sciences | 23 | 10% |
| Psychology | 21 | 10% |
| Engineering | 8 | 4% |
| Other | 18 | 8% |
| Unknown | 75 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 March 2019.
All research outputs
#16,720,137
of 25,371,288 outputs
Outputs from Behavior Research Methods
#1,538
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Outputs of similar age
#162,066
of 286,441 outputs
Outputs of similar age from Behavior Research Methods
#20
of 44 outputs
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