Title |
TACIT: An open-source text analysis, crawling, and interpretation tool
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Published in |
Behavior Research Methods, March 2016
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DOI | 10.3758/s13428-016-0722-4 |
Pubmed ID | |
Authors |
Morteza Dehghani, Kate M. Johnson, Justin Garten, Reihane Boghrati, Joe Hoover, Vijayan Balasubramanian, Anurag Singh, Yuvarani Shankar, Linda Pulickal, Aswin Rajkumar, Niki Jitendra Parmar |
Abstract |
As human activity and interaction increasingly take place online, the digital residues of these activities provide a valuable window into a range of psychological and social processes. A great deal of progress has been made toward utilizing these opportunities; however, the complexity of managing and analyzing the quantities of data currently available has limited both the types of analysis used and the number of researchers able to make use of these data. Although fields such as computer science have developed a range of techniques and methods for handling these difficulties, making use of those tools has often required specialized knowledge and programming experience. The Text Analysis, Crawling, and Interpretation Tool (TACIT) is designed to bridge this gap by providing an intuitive tool and interface for making use of state-of-the-art methods in text analysis and large-scale data management. Furthermore, TACIT is implemented as an open, extensible, plugin-driven architecture, which will allow other researchers to extend and expand these capabilities as new methods become available. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Switzerland | 1 | 25% |
United States | 1 | 25% |
Unknown | 2 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 3 | 75% |
Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | <1% |
Austria | 1 | <1% |
Australia | 1 | <1% |
Unknown | 123 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 22 | 17% |
Student > Master | 21 | 17% |
Student > Bachelor | 21 | 17% |
Professor | 10 | 8% |
Student > Doctoral Student | 9 | 7% |
Other | 23 | 18% |
Unknown | 20 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 44 | 35% |
Computer Science | 19 | 15% |
Social Sciences | 14 | 11% |
Linguistics | 4 | 3% |
Medicine and Dentistry | 4 | 3% |
Other | 19 | 15% |
Unknown | 22 | 17% |