webQDA software case study: analysis of qualitative data in a collaborative anddistributed environment

António Pedro Costapcosta@ludomedia.pt; apcosta@ua.pt

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Session Goals

•Research collaboratively through web-based software•Present training models to decrease the learning curve in

the use of CAQDAS•Analyze qualitative data (text, image, video and audio) of

different formats (i.e. pdf, mp4, png)

Research

More(Quantity)

Better(Quality)

5

Subjectivity and Context

6

Challenges of qualitative research

• Diversity of research settings.• Diversity of formats and data types.• Large amounts of data.• Conjunction with quantitative methodologies (Mixed Methods).• Complexity in triangulation analysis.• Working in multidisciplinary and international groups.• Greater demand for transparency and validation of processes and results.• Integration of Information Communication Technology in all phases of the study.• ... etc.

Challenges of Qualitative Data Analysis Software (QDAS)

• Enable direct work with various formats and data types.• Robustness to deal with large amounts of data.• Allow for greater flexibility in performing tasks.• Enable collaborative work in large and small groups.• Simplicity to reduce the learning curve of the tools.• Greater compatibility and portability of data and analysis processes.

QDAS brief history• In 1966, MIT developed a software called "The General Inquiry" to help text analysis.

• In 1984, Ethnograph software emerges.

• In 1987, Richards & Richards developed the Non-Numerical Unstructured Data Indexing Searching and Theorizing software (NUD*IST). It evolved into the current NVivo.

• In 1991, the ATLAS-ti prototype was launched, mainly related to Grounded Theory.

• In the transition of the 2000s, it was possible to integrate video, image, audio and text in the analysis. However, HyperRESEARCH had been presented before. Meantime, Transcriber and Transana are other software systems that were developed.

• In 2004, NVivo provided an overview of some of the previous software with striking features, such as the Atlas-ti– it recovers encoding by in vivo and Ethnograph – a visual presentation coding system.

• 2009 marks the beginning of the software development in computer contexts in the cloud. Examples are Dedoose and webQDA, which were developed almost simultaneously in the US and Portugal, respectively.

• From 2013 onwards, we saw an effort by software companies to develop versions for iOS, incorporating data from social networks, multimedia and other visual elements in the analysis process.

Qualitative data

• Clinical reports• Personal documents• Field notes• Photographs• Videos• Subject’s discourse• Oficial Documents• …

Observation

InterviewsDocuments

What is data analysis in Qualitative Research?

•Working with data• Organizing data• Dividing data into manageable units• Data synthesis

• Looking for patterns• Discovery of the important aspects of data• Discovery of what should be learned from the data• Deciding how to transmit data to others

Without software

Without specific software

How to Choose a QDAS?• Pinho, I., Rodrigues, E., Neri de Souza, F., & Lopes, G. (2014). Determinantes na

Adoção e Recomendação de Software de Investigação Qualitativa: Estudo

Exploratório. Internet Latent Corpus Journal, 4(2), 91–102.

• ResearchGate: “Can you recommend a software for analysing qualitative data

(interview transcripts)?” https://www.researchgate.net/post/Can_you_recommend_a_software_for_analyzing_qualitative_data_interview_transcripts

• There is a long set of literature addressing this issue, some more biased than other, but that do not fail to give their valuable contribution.

Valued features of QDAS

Ease of use

Adequate functionalities

Contribution towards research

Good price/quality ratio

Ease of learning

Inadequatefunctionalities

Bad price/quality ratio

Ease of learning

Difficulty of use

Lack of compatibility

Female Male Female Male

Satisfaction factors Disatisfaction factors

(Pinho, Rodrigues, Neri de Souza, & Lopes, 2014)

What do we look for in a CAQDAS?CAQDAS refer to software packages which include tools designed to facilitate a qualitativeapproach to qualitative data analysis.Qualitative data includes texts, graphics, audio or video. CAQDAS packages may also enablethe incorporation of quantitative (numeric) data and/or include tools for adopting quantitative approaches in qualitative data analysis.

• Content searching tools• Linking tools• Coding tools• Query tools• Writing and annotation tools• Mapping or networking tools

Cf. Lewins & Silver, 2009

• .• AQUAD • ATLAS/ti• CoAn• Code-A-Text• DICTION• DIMAP-MCCA• HyperRESEARCH• KEDS• DEDOOSE

• NUD*IST• NVivo• QED• TATOE• TEXTPACK• TextSmart• Transana• WinMaxPro• WordStat

webQDA history and partnerships

• 2010

• 2015

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• Authors• António Pedro Costa (pcosta@ludomedia.pt)• António Moreira (moreira@ua.pt)• Francislê Neri de Souza (fns@ua.pt)

• Software designed to assist researchers to handle non-numeric and unstructured data in qualitative analysis.

•With webQDA the researchers can edit, view and link documents. They can create categories, encode, manage, filter, query and question the data in order to answer research questions.

• In academic contexts, webQDA is especially useful for researchers, graduation,

master's and doctorate students, as well as for research teams to develop

synchronous and asynchronous analysis of qualitative data in collaboration,

from any device connected to the internet.

• In a business context, webQDA is especially useful for analysis of non-numeric

and unstructured data, for example, customers’ opinions about a product or

an advert.

webQDA is to qualitative research and SPSS to quantitative

research, as the word-processor (word) is for writing. In any

case the human factor is always critical.

"My text editor doesn’t write alone."

Before and During the use of webQDA

• Sound Research Questions;• Feasible Research Objectives;• Comprehensive Theoretical Framework;• Validate Data Collection Instruments;• Careful and Systematic Transcriptions;• Well Structured Data Organization;• Etc.

FAQ’s

•What are the types of research that I can use with webQDA?•What research designs should I use with webQDA?• How does the use of webQDA differ from traditional research tools

and qualitative analysis?•Will I spend less time analysis using webQDA?• Can the use of webQDA improve the quality of my work?• I have only two interviews. Is it worth spending time to learn how to

use webQDA?

Unconfirmed expectations

• Introduction and coding of data is laborious and time consuming,or at least slower than you might expect (no software, is worse).• High dependence on the continued work of the researcher -most tasks can not be delegated.• Do not expect to present innovative solutions as we apply aformula, as it would happen if we used sophisticated statisticalmethods.

Main areas in webQDA

Elements for the Writingof Results in Qualitative Analysis

Procedural structure in webQDA

• Coding procedures• Contextualization procedures

1. Source System

2. Coding System

3. Questioning System

• Validation procedures• Inference procedures

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Technical Specifications• Respects the HTML5 standard that is supported by most popular web browsers

(Internet Explorer, Firefox, Safari, Chrome, Opera).

• Permissions for use of Cookies is also a requirement and the browser must be allowed to run JavaScript.

• For a better user experience we recommend a resolution of at least of 1280 x 720.

• Sources requirements:• Text Sources: DOCX, PDF, XLS and TXT (Maximum size of 1MB per file)• Image sources: JPG and PNG (Maximum size of 5MB per file)• Audio sources: MP3 and WAV (Maximum size of 10MB per file)• Video sources: MP4, OGG and WEBM (Maximum size of 20MB per file)• You can use YouTube videos, or videos from public sharing of Dropbox.

News features

• Social Network Analysis• Clusters• Actors• Organizations• …

News features

• Sentiment Analysis Methods

Conferences

• www.ciaiq.org

• 2018 – Fortaleza, Brazil

• 2017 edition (about 700 submissions) – Salamanca, Spain

• 2016 edition (about 800 submissions) – Porto, Portugal

• 29 countries

• more than 30 partner journals (most indexed SCOPUS and / or ISI)

Conferences

• www.wcqr.info• 2018 – Lisbon, Portugal (World Conference on Qualitativa Research)• 2017 – Salamanca, Spain (2nd International Symposium on Qualitativa

Research)• 2016 – Porto, Portugal (1st International Symposium on Qualitativa Researc

webQDA software case study: analysis of qualitative data in a collaborative anddistributed environment

António Pedro Costapcosta@ludomedia.pt; apcosta@ua.pt

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