Best Software For Qualitative Data Analysis Mac
All-in-one Content Analysis Software Use MAXQDA to manage your entire research project. Easily import data from texts, interviews, focus groups, PDFs, web pages, spreadsheets, articles, e-books, and even tweets. Organize your data in groups, link relevant quotes to each other, and share and compare work with your team members. Dovetail is a new qualitative research analysis and collaboration tool designed specifically to analyse free text survey answers. We’re not open source, but we do run on Mac because we’re cloud-based. Our product page covers our features in detail, but here's a short list of the things you can do with Dovetail. You have a good range of qualitative data analysis methods to choose from, in order to achieve the main purpose of qualitative analysis – to explain, understand, and interpret data. There are many software solutions (such as Atlas.ti ) designed to assist you with the analysis of qualitative data. Jun 03, 2020 Qualitative Software Overview and Comparison by GMU Data Services; CAQDAS (Computer Assisted Qualitative Data AnalysiS) Networking Project. Software-focused site by the Sociology Department at the University of Surrey; Includes help on choosing software and news on the most popular packages. Here you can find a compilation of what that site calls the top 21 free qualitative data analysis software. Some I have heard of, som not. Some can handle both audio and video data. JMP is the tool of choice for scientists, engineers and other data explorers in almost every industry and government sector. JMP combines dynamic data visualization with powerful statistics, in memory and on the desktop. Interactive and visual, JMP reveals insights that raw tables of.
As data is an invaluable source of business insight, the knowing what are the various qualitative data analysis methods and techniques has a crucial importance.
There are different approaches, types of statistical methods, strategies, and ways to analyze qualitative data.
Choosing the best way and technique depends on the nature of your data and the goals set in qualitative research.
On this page:
- What is qualitative data analysis? Definition.
- Techniques and methods used in qualitative data analysis: list and explanation.
- Infographic in PDF.
What is qualitative data analysis?
Let’s define it:
Qualitative Data Analysis (QDA) involves the process and procedures for analyzing data and providing some level of understanding, explanation, and interpretation of patterns and themes in textual data.
Just to recall that qualitative data is data that can’t be expressed as a number. Qualitative data consist of words, pictures, observations, and symbols, not numbers. For more details see our post qualitative vs quantitative data.
Generally, QDA has 4 main steps:
- Becoming familiar with your data. You need to read and re-read the data, write down detailed notes and impressions, and deciding which pieces of data possess value.
- Coding into themes – this means to create categories and subcategories. Each category is an example of some thematic idea. The goal is to group data associated with some thematic idea which allows them to be examined together. The list of build themes represents your first set of codes.
- Searching for patterns and connections – looking for the relative importance of data and identifying relationships between data sets or themes.
- Interpretation of the data and drawing conclusions.
Qualitative Data Analysis Methods And Techniques
There are a wide variety of qualitative data analysis methods and techniques and the most popular and best known of them are:
1. Grounded Theory Analysis
The grounded analysis is a method and approach that involves generating a theory through the collection and analysis of data. That theory explains how an event or aspect of the social world “works”.
Grounded theory is one of the most popular qualitative strategies that leads to a general, abstract theory of a process or action grounded in the views of people that participate in a study.
The main feature of the grounded theory, which differentiates it from other qualitative data analysis methods is its focus on theory development.
Grounded theory technique is very suitable to use, especially when you have to analyze large quantities of unstructured qualitative data. (to know what unstructured data mean see our post unstructured data examples).
Key data collection methods and techniques that Grounded theory uses:
- Interview with open-ended questions
- Focus groups
- Participant observation
- Study of texts
Note: data analysis in Grounded theory happens at the same time as data collection. It means you shouldn’t wait until all your data is collected and then analyze it. The methods have to be flexible and change when the data show a new theory or direction.
2. Content Analysis
Content analysis is one of the most widely used qualitative data techniques for interpreting meaning from text data and thus identify important aspects of the content.
It includes processes and procedures for the categorization of text data for the purpose of classification and summarization.
The text can be various formats such as documents, pictures, video, audio, and etc.
The most popular application of content analysis nowadays is in analyzing the social media field. It is used to quantify patterns and trends in social media communication.
You will be surprised with the broad range of content analysis software solutions today. They help you to examine almost any type of unstructured text data such as business documents, emails, social media, chats, comments, news, blogs, and much more.
In addition, the machine learning classification algorithms can significantly increase the amount of text which can be labeled and classified.
Key purposes of content analysis are:
- To find out important aspects of the content.
- To present them in a clear and effective way.
- To support some argument.
In fact, content analysis is not a single method. It has popular techniques and approaches: conventional, directed, or summative. The main differences among the techniques are origins of codes and coding schemes.
3. Narrative analysis
Narrative analysis is also one of the best-known qualitative data analysis methods and techniques.
Narrative analysis is an approach to analyzing different stories people create. The purpose is to understand how people form meaning in their lives as narratives.
It uses various types of stories such as autobiography, family stories, photos, life experience, as the units of analysis. It focuses on the ways in which people create and use different stories to interpret and explain the daily life and the world.
What can we discover from the narrative analysis?
- An interesting knowledge and understandings about people, their culture and how they are changing.
- It helps us making sense of the past and create meanings of it.
- Helps in organizing information about how humans interpret events.
- Show us the values and beliefs that guide those interpretations.
A long number of data collection methods can be performed. Data can be in the form of journal records, interview transcripts, observations, autobiographical writing, documents, storytelling, personal accounts, letter writing, and etc.
4. Discourse Analysis
Discourse analysis is about analyzing the natural occurring talk – spoken communication and all other types of text.
It studies the meanings that the use of language and spoken interactions produce and the contexts of these meanings.
This method not only analyses communications but also takes into consideration the social context in which the communications happen.
This technique can also include analysis of written texts, such as emails or the body language.
Discourse analysis is a field of linguistics that focuses on the role of language in the building of social reality.
Typically, discourse analysis brings together the analysis of language use and the analysis of situations.
5. Framework Analysis
Framework is one of the qualitative data analysis methods that are gaining popularity across multiple areas, including health, social policy, and psychology.
This approach is used to organize and manage data with the help of the process of summarization. It results in a powerful and flexible matrix that allows you to analyze data both by theme and case.
The matrix consists of rows (cases), columns (codes) and ‘cells’ of summarised data. Thus it provides a structure into which you can systematically cut the data, to analyze it by case and by code.
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Using theme display, framework technique lets you analyze your data thematically and to perform exploratory analysis of the entire dataset.
Framework analysis identifies similarities and differences in qualitative data, thereby aims to draw descriptive or explanatory conclusions grouped in themes.
Framework analysis is one of the easiest qualitative data analysis techniques.
It has very clear steps you can follow and makes highly structured outputs of summarised data.
Conclusion
You have a good range of qualitative data analysis methods to choose from, in order to achieve the main purpose of qualitative analysis – to explain, understand, and interpret data.
There are many software solutions (such as Atlas.ti) designed to assist you with the analysis of qualitative data.
Moreover, for the advanced users, there is a free qualitative data analysis software able to analyze a large amount of text.
They have enhanced people’s ability to perform data analysis by handling multiple means and ways of collecting, sorting, presenting, and analyzing raw data.
Frankly speaking, there isn’t a long list of free qualitative data analysis software for MAC. Still, there is a choice of tools to help you sort, organize and analyze a large amount of text or other types of data.
Nowadays, computer-assisted qualitative data analysis software (CAQDAS) is a must for researchers and data professionals. You can use it to analyze a focus group transcripts, journal articles, legal documents, books, images, paintings, and many other types of information.
Of course the free options have a lot of limitations but still, you can use them to get done a lot of work. Here is a list of the best free qualitative data analysis tools for MAC, you can consider if you lack the budget.
1. RDQA
RDQA is a R package for Qualitative Data Analysis, and it is a free qualitative analysis software application ( with BSD license). It works on Linux/FreeBSD, Mac OSX and Windows.
You can use it to enter data into a database and codify the data by 4 levels: cases, codes, code categories, and annotations. RDQA is used mainly by small and midsize organizations but it also has large enterprise users.
RDQA is easy to use tool by many statisticians and data experts when performing analysis of textual data. However, for now, it only supports just plain text formatted data.
Kye features and benefits:
- Import documents from plain text or on-the-fly
- Import PDF highlights.
- Support non-English documents.
- File Editing after coding.
- Advanced Graphic user interface.
- Memos of documents, coding, project, codes, files and more.
- Single-file (*.rqda) format, which is basically a SQLite database.
- Organize codes into code categories, which is key to theory building.
- Organize files into file categories.
- Apply attributes to file, which is useful for content analysis.
- Rename files, codes, code categories, and cases
- Calculate the relation between two codings, given the coding indexes
- Give a summary of coding and inter-code relationships
And more … - Website: http://rqda.r-forge.r-project.org/
2. TAMS Analyzer
When it comes to free qualitative data analysis software for MAC, this is one of the most popular choices. TAMS (stands for Text Analysis Markup System) is an open source tool that allows you to quickly code sections of text.
The software runs on Macintosh and Linux platforms.
Despite TAMS is generally employed to encode discourse and ethnographic documents (such as interviews), you can also use it to analyze almost any plain text.
You can import documents, fields notes or interview transcript and seamlessly code them by clicking on code from your list.
The Macintosh version of the program also includes full support for transcription (back space, insert time code, jump to time code, etc.) when working with data on sound files.
Key features and benefits:
- PDF coding and analysis support
- Image (jpg, etc.) coding
- Layout for video coding
- Multi-user support using MySQL as a server
- Multimedia support
- XML file formats
- Hot code sets
- Ability to set comments for both ranges of text and individual tags
Many others…. - Website: http://tamsys.sourceforge.net/
3. HyperRESEARCH
HyperRESEARCH is a flexible and powerful tool that assists you in data analysis and theory building. From coding and retrieval to analysis and reporting, the tool got you covered.
HyperRESEARCH is an intuitive software solution that requires near-zero learning curve to help you get started. The program is for MAC and Windows and allows you to move your work seamlessly between Mac and Windows.
They offer premium and free option. You can download the Free Limited Edition. The size and complexity of your study is limited, but otherwise, you can access all the features. You can use the Free Limited Edition as long as you like.
Key features and benefits:
- Very easy to use – you can start coding right away with simple, intuitive steps.
- Any piece of data in a source for coding—text, image, audio, video, or PDF (coming soon).
- Go beyond coding and categorizing—use the Theory Builder to frame and test a hypothesis.
- See your codes in the margin of your data for easy scanning.
- Protect privacy by automatically masking sensitive information.
- Many others….
- Website: http://www.researchware.com
4. QDA Miner Lite
QDA Miner Lite is also one of the top free qualitative data analysis software for MAC.
You can use the tool for the analysis of textual data (such as interview and news transcripts), open-ended answers from a market research, as well as for the analysis of still images.
Generally, QDA Miner Lite is a Windows application. However, there are ways to run it on a Mac OS computer.
Key CAQDAS features and benefits:
- Importation of documents from plain text, RTF, HTML, PDF and also data from Excel, MS Access, CSV, and other text files.
- Importation from transcription tools and from other qualitative coding software such as Altas.ti, HyperResearch, and many others.
- Intuitive coding using codes organized in a tree structure.
- Code frequency analysis with charts and tag clouds.
- Export tables to XLS, Tab Delimited, CSV formats, and Word format.
- Export graphs to BMP, PNG, JPEG, WMF formats.
- Interface and help file in English, French, and Spanish.
- Website: https://provalisresearch.com/
5. KH Coder
KH Coder is a free software for qualitative data analysis, quantitative content analysis, and text mining for MAC and Windows. The tool provides a variety of statistical analysis functions by using MySQL, ChaSen, and R as back-end tools.
You can analyze Japanese, English, French, German, Italian, Portuguese, Spanish, Chinese (simplified), Korean and Russian language data and text with KH Coder.
Free Qualitative Software Analysis Tool
KH Coder provides an opportunity for a variety of types of statistical analysis and functions using tools such as Stanford POS Tagger, Snowball stemmer, MySQL and R.
Key features and benefits:
Qualitative Data Analysis Software Reviews
- Qualitative and quantitative analysis.
- Text meaning.
- Utilized for computational linguistics.
- On word-level: frequency list, searching, KWIC concordance, collocation stats, correspondence analysis…
- On category-level: developing your own categories, frequency list, cross tabulation, correspondence analysis, multi-dimensional scaling…
- On documents level – searching, clustering, and naive bayes classifier.
- Website: http://khc.sourceforge.net/en/