Analyzing Social Media Data Using NVivo 11: A Hermeneutic Phenomenological Approach

(HPA)

Philip Adu, Ph.D.

Methodology Expert

National Center for Academic & Dissertation Excellence (NCADE)

The Chicago School of Professional Psychology

padu@thechicagoschool.edu

@drphilipadu

Main Focus of this Presentation

Hermeneutic phenomenological approach (HPA)• Meaning

• Characteristics

• Application

• Collecting and Analyzing Twitter Data• STEP 1: Gather Twitter data

• STEP 2: Conduct data cleaning

• STEP 3: Upload the data into NVivo

• STEP 4: Reorganize the data

• STEP 5: Conduct data exploration (using ‘Query’ command)

• STEP 6: Start coding relevant information in the data

• STEP 7: Generate themes to address the research questions

Phenomenological Approach

Give participants the chance to talk about what they have

experienced

Examine the participants’ experiences

Determine the essence of their experiences

(Kafle, 2013)

Two Main Types of Phenomenological Approach

Transcendental phenomenological approach (focus on attaining objectivity)

1. Suspending all the biases you have (i.e. epoche)

2. Collecting participants’ experiences

3. Examining and describing participants’ experiences

Hermeneutic phenomenological approach (focus on attaining subjectivity)

1. Being aware of all your biases

2. Making a conscious effort to bracket your biases

3. Examining subjective experiences (stories) for understanding

4. Interpreting participants stories

(Kafle, 2013)

Hermeneutic Phenomenological Approach

Meaning

• Examining and “understanding text” (pp. 190)

• The text normally depicts participant’s:• Experience

• Perspective of the experience

• Thoughts and feelings about a phenomenon

• Intent/purpose

(Kafle, 2013)

Hermeneutic Phenomenological Approach

Characteristics

It involves:1. Suspending your pre-knowledge (but it is challenging)2. Making your preconceptions, beliefs, biases, and background

known3. Examining and reflecting on the texts4. Acknowledging multiple perspectives and interpretations of the

texts5. Attaining understanding and underlying meaning of the texts

(Kafle, 2013)

Hermeneutic Phenomenological Approach

Application (Intense examination of the data from twitter)

It involves:Reviewing each ‘tweet’ – examining:

1. Meaning of the ‘tweet’

2. Possible intent of the writer (i.e. sender of the ‘tweet’)

3. Possible audiences of the message (‘tweet’)

4. Interpretation of the 'tweet'

5. Relevance of the interpretation in addressing the research question

(Kafle, 2013)

About Social Media (Twitter)

• Create a message • Adopt an original message

• Create a hashtag [i.e. word/phrase with a pound sign(#)]• Adopt a hashtag (#)

• Attach it to the message before tweeting

• Share the tweet to their twitter followers

Construct

Label

Share

Collecting and Analyzing Twitter Data

• STEP 1: Gather Twitter data

• STEP 2: Conduct data cleaning

• STEP 3: Upload the data into NVivo

• STEP 4: Reorganize the data

• STEP 5: Conduct data exploration (using ‘Query’ command)

• STEP 6: Start coding relevant information in the data

• STEP 7: Generate themes to address the research questions

Source: http://www.slideshare.net/kontorphilip/conducting-qualitative-analysis-of-

social-media-twitter-data-using-nvivo-11

Collecting and Analyzing Twitter Data(STEP 1: Gather Twitter data)

1. Review your research questions

2. Determine what kind of data you need from the social media (Twitter)

3. Come up with key words/phrases that you would use to search for the information you need from Twitter

4. Search with key words/phrases using a pound sign (#) e.g. #mentalhealthcare

5. Review the search results to determine the richness of the data in addressing your research questions

6. Click on the ‘Ncapture’ icon to download the data

Note: You need to install the ‘Ncapture’ icon on your web browser

For an ‘Internet Explorer’ browser, go to: http://help-ncapture.qsrinternational.com/desktop/topics/install_ncapture_for_internet_explorer.htm

For a ‘Chrome’ browser, go to: http://help-ncapture.qsrinternational.com/desktop/topics/install_ncapture_for_chrome.htm

Collecting and Analyzing Twitter Data(STEP 2: Conduct data cleaning)

1. Import the data into NVivo

2. Export the data in Excel format

3. On the Microsoft Excel spreadsheet, delete unnecessary columns NOTE: If you have a lot of tweets of analyze, you could randomly select a number of

tweets for the analysis. More information about conducting random sampling: https://www.youtube.com/watch?v=q8fU001P2lI

4. Save and close the spreadsheet

5. Assign anchor codes to the research questions• Example:

• What should be done to combat mental health stigma? (Combating mental health stigma)

• How do twitter users perceive mental health stigma? (Perspectives on mental health stigma)

Collecting and Analyzing Twitter Data(STEP 3: Upload the data into NVivo)

1. Import the Excel dataa. Clicking on ‘DATA’

b. Going to ‘Survey’

c. Clicking on ‘From Microsoft Excel File…’

Collecting and Analyzing Twitter Data(STEP 4: Reorganize the data)

Select the data (from your computer) you plan to import and follow the instructions

• There are three main files/storages (‘containers’) the NVivo software would create:

• Case – Contains characteristics associated with each tweet (Note: the unit of analysis would be the ‘tweet’)

• Case classification - Contains variables/attributes associated with the tweets that won’t be coded. In NVivo, ‘attributes’ are the categorical variables, and ‘values’ are groups under attributes.

• Example

• ‘Tweet Type’ (i.e. ‘Attribute’)

• ‘Retweet’ (i.e. ‘value’)

• Node - Container that keeps actual tweets which will be coded

Collecting and Analyzing Twitter Data(STEP 5: Conduct data exploration (using ‘Query’ command))

Run a Query (i.e. conducting an initial analysis)

Word Cloud

Word Tree

Collecting and Analyzing Twitter Data(STEP 6: Start coding relevant information in the data)

1. Review each 'tweet' examining:1. Meaning of the 'tweet'

2. Possible intent of the writer

3. Potential interpretations of the 'tweet‘

2. Decide on the best interpretation1. Determine what the best interpretation is in addressing the research

question

2. Create a label to represent the tweet (i.e. creating a node)

1. Alternatively, you could drop the relevant tweet into an existing node

3. Repeat this process for all the tweets compiled

Collecting and Analyzing Twitter Data(STEP 6: Start coding relevant information in the data)

Example: Tweet: “I just need a hug.....from someone who doesn't know I have Bipolar so I can be

treated equally.... #mentalhealthstigma #imnotdifferent”

Research question: What should be done to combat mental health stigma? (Combating mental health stigma)

Meaning Intent Interpretation

(in terms of addressing the

research question)

Node

• Don’t treat people differently

because they have mental

illness

• People with mental illness such

as bipolar are not a threat

• Promote

acceptance

and equal

treatment

• Show compassion to those

who have mental illness

• Avoid discrimination against

people with mental illness

Equal treatment

irrespective of the

mental health

condition

Collecting and Analyzing Twitter Data(STEP 6: Start coding relevant information in the data)

Example: Tweet: “"Mental illness is nothing to be ashamed of, but stigma and bias shame us all."

#mentalhealthstigma #mentalillness”

Research question: How do twitter users perceive mental health stigma? (Perspectives on mental health stigma)

Please complete the table below:

Meaning Intent Interpretation

(in terms of addressing the

research question)

Node

What is the meaning of the tweet? What is the

writer of the

tweet?

What is the interpretation of

the tweet in terms of

addressing the research

question?

What is the node

(label or code) for

the tweet?

Collecting and Analyzing Twitter Data(STEP 7: Generate themes to address the research questions)

After the initial coding process, you could categorize the data based on their similarities, frequencies (i.e. how many times the code is assigned to specific parts of the data).

For more information go to: http://www.slideshare.net/kontorphilip/qualitative-analysis-coding-

and-categorizing (see Slide 17)

References

Adu, P. (2016, October 22). Conducting Qualitative Analysis of Social Media (Twitter) Data Using NVivo 11. Retrieved from http://www.slideshare.net/kontorphilip/conducting-

qualitative-analysis-of-social-media-twitter-data-using-nvivo-11

Kafle, N. P. (2013). Hermeneutic phenomenological research method simplified. Bodhi: An Interdisciplinary Journal, 5(1). doi:10.3126/bodhi.v5i1.8053

Philip Adu, Ph.D.

Methodology Expert

National Center for Academic & Dissertation Excellence (NCADE)

The Chicago School of Professional Psychology

Ncade.me@thechicagoschool.edu

You could reach me at padu@thechicagoschool.edu and @drphilipadu on twitter.

To cite this document, copy the following:

Adu, P. (2016, October 22). Analyzing social media data using Nvivo 11: A hermeneutic phenomenological

approach. Retrieved from http://www.slideshare.net/kontorphilip/analyzing-social-media-data-using-nvivo