Saher Chaudhry - 2021 Student Research and Creativity Forum - Hofstra University

Micro-Level Analysis of Tinnitus Data on Social Media Platforms: Facebook and Twitter Aniruddha K. Deshpande, Saher Chaudhry, & Vinaya Manchaiah

What is Tinnitus?

Tinnitus is the perception of a phantom sound that some people experience in the absence of any external auditory stimuli. It is often described as a ringing, buzzing, or hissing sound. It is a debilitating condition that may affect as many as 42% of older adults (Gibrin et al., 2013).

Reaching Out...

Because of the challenges already presented in seeking professional treatment, it is plausible for affected individuals to feel encouraged to seek information about tinnitus online and build personal satisfaction in health decision-making and management (Broom, 2005). Seeking information online comes at a cost.

Previous studies The quality and readability of online tinnitus-related information have also been investigated by our group (Deshpande et al., 2018; Deshpande et al., 2019).

Manchaiah et al (2018) analyzed information in newspaper media between 1980 and 2017 and have discovered a shift toward covering more tinnitus-related innovations in the later years of their study period: ● Readability of several tinnitus websites and found that 10-12 years of education is needed to properly understand the information on these websites. ● A macro-analyses has been conducted to determine tinnitus information trends on search engines and social media platforms. ○ Facebook is one of the most popular platforms for tinnitus related content. ○ Abundance of misinformation.

What We Aim to Study Types of Facebook pages that contain tinnitus-related content and the prevalence of spam/misinformation pages.

Prominent key words related to tweets containing the word “tinnitus” and the prevalence of misinformation.

Purpose Aim 1

Analysis of micro-level trends on two community-centered social media platforms: Twitter and Facebook.

existing 01 Expand studies

02 Conduct a micro-analysis

Aim 2

Identify how tinnitus-related information is shared, spread, and popularized on social media.

Aim 3

Identify, quantify, and categorize misinformation on the studied social media platforms.

Analytic Tools

Netlytic Collect hashtag/keyword trends regarding tweets that contain the word “tinnitus” on Twitter

Popsters Investigate the type, popularity, and number of pages that frequently share tinnitus-related information on Facebook

Types of Facebook Pages

Micro Trends on Facebook

N

Average Followers

Average ER Day

Average ER Post

Average LR

Average TR

Organizations

3

11,898

0.85

0.96

0.82

0.04

Support Groups

2

2,964

0.18

0.31

0.10

0.20

Informational

1

2,268

0.40

0.40

0.27

0.09

Clinics

5

1,930

0.16

0.26

0.23

0.02

Engagement Rate (ER) measures the degree of engagement among followers to posted content.

Like Rate (LR) measures identify the relative appeal of the posts in regards to the number of likes.

Talk Rate (TR) measures the sociability of the posts by analyzing the number of comments of the posts to indicate the audience involvement in communication.

Analyzing Twitter Data via Netlytic Collect and import data that contains the keyword “tinnitus” in tweets from 03/08/21 to 04/08

After 30 day collection, Tweets were analyzed based on the resulting categories that Netlytic automated.

11 resulting manual categories were observed and reviewed for further analysis.

Data exported to Excel, where a total of 6,998 tweets are recorded and further organized. All tweets were read and filtered based on relevancy to tinnitus.

Additional categories were self-made and inputted into the Netlytic tool to further aggregate data associated with the added categories.

Number of weekly Tweets from 03/08 to 04/08

Total Tweets: 6,998

Manual Categories: Automated and Self-Made Feelings (Bad) N = 1276

Sound N = 162

Original Tweets: 228 Retweets: 631

Original Tweets: 17 Retweets: 10

Original Tweets: 13 Retweets: 155

Feelings (Good) N = 716

Time N = 301

Community N = 755

Original Tweets: 228 Retweets: 76

Original Tweets: 107 Retweets: 94

Original Tweets: 224 Retweets: 314

Quantity N = 368

Noise N = 776

Shape N = 250

Original Tweets: 86 Retweets: 127

Original Tweets: Retweets

Original Tweets: 87 Retweets: 52

Healthcare N = 66

Appearance N = 2138 Original Tweets: 472 Retweets: 134

Health N = 190

Original Tweets: 32 Retweets: 16

Facebook With Facebook advantage in providing professionals and organizations a platform to share informational content, several inferences can be made in Facebook pages from March 8th to April 8th: ○ Organizations dominate tinnitus related social activity with having the highest number of followers, engagement rate, like rate, and talk rate. ○ Lower overall social engagement in this platform compared to Twitter

Twitter With Twitter’s advantage in providing individuality for users, several inferences can be made in twitter users’ behaviors from March 8th to April 8th: ● Many twitter users expressed grief, empathy, and devastation in response to a news article describing a businesse ownder committing suicide due to his dehabiliting symptoms of tinnitus. ● COVID-19 was one of the most prominent subject in tweets. ○ Misinformation were largely shared in these tweets. ● Greater sharing of studies and articles associated with tinnitus. ○ A large number of tweets contained identical descriptions of studies and news article.

Twitter Twitter engagement mostly consists of individual users who post tweets that are personal- describing wellbeing, challenges with tinnitus, and their input on tinnitus related news. Compared ton organizations or businesses, individuals with tinnitus shared a greater number of tweets, resulting in less credible information to be present on Twitter.

Spam and unreliable tweets were highly frequent, though these tweets would receive few shares and likes.

Facebook Social media engagement is more prominent in organizations and associations that promote and bring awareness to tinnitus.

Additionally, healthcare professionals and businesses have a greater presence on Facebook by advertising their services and products.

Spam/unreliable pages share less frequent content, with several pages not having to post in more than a year.

Limitations

Tools Though reliable, Analytic tools do not always produce accurate categorization results; additional reviewing and examination of the data is required to generate conclusions with the data.

Time Narrow data collection period; Data was only collected in a span of a month (03/21 to 04/21).

Future studies can widen this time period following with a micro-analysis.

Inclusivity Data does not include private facebook pages and tweets. Future studies can conduct a micro analysis with the addition of these private communities/users.

Future Directions ●

Upcoming research on Instagram and YouTube. ○ Received funding for summer 2021 from Faculty Research Development Grant 2021.

■ Principal Investigator (PI) Dr. Aniruddha Deshpande.

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Upcoming research on studying tinnitus related content associated with the COVID-19 Pandemic, especially on Twitter. ○ Study data starting from March 2020 to current.

Future research can review different analytical tools aside from Netlytic and Popsters to study tinnitus related content on major social media platforms. ○ Delve into different methodologies and tools to replicate this study.

Future research can expand time period of the study to more than a month.

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Thank You!