Michael Okun

Michael Okun

@MichaelOkun

National Medical Advisor @parkinsondotorg Author 14 books https://parkinsonsecrets.com/ blog Professor @UF @fixelinstitute Associate Editor @JAMANeuro @DBSThinkTank

Gainesville, FL https://www.parkinson.org/about-us/leadership/national-medical-advisor Joined 2013-07-02 Date of Analysis: Dec 16, 2025

33,400

Followers

3,765

Following

14,653

Tweets

66.8

Avg Engagement

160

Listed

No

Verified

Account Overview

What This Report Covers

This comprehensive analysis examines @MichaelOkun's Twitter/X presence across multiple dimensions. We analyze tweet content, engagement patterns, audience demographics, posting habits, and network connections to provide actionable insights about this account's social media strategy and influence.

Account Classification

  • Account Size: Mid-Tier (10K+)
  • Account Age:2013-07-02
  • Verification:No
  • Location:Gainesville, FL

Data Summary

  • Tweets Analyzed:500
  • Avg Likes per Tweet:13.5
  • Avg Retweets per Tweet:53.3
  • Followers Analyzed:22,621

Engagement Analysis

Based on 500 tweets

His tweets typically receive moderate engagement, with an average of 111 likes and 28 retweets. The content often sparks discussion, especially around complex medical topics.

13.5

Avg Likes/Tweet

53.3

Avg Retweets/Tweet

6,773

Total Likes

26,632

Total Retweets

Engagement Quality Analysis

Median-based metrics that resist fake virality and outliers.

6

Median Likes

5

Median Retweets

35

75th Percentile

4,856

Top Tweet

2.0

Engagement per 1K Followers

Normalized influence metric

Viral Spikes

Engagement Pattern

Few posts get most engagement

Posting Behavior

Content style and format preferences

Curator

Amplifies others content frequently

49.2%

Original

2.4%

Replies

41.2%

Retweets

7.2%

Quotes

0.0%

Threads

0.0%

With Media

59.0%

With Links

29.8%

With #Tags

70.8%

With @Mentions

1.6%

With Emojis

215

Avg Length

Audience Reaction Profile

Broadcast

Focuses on original content over replies

0.05

Reply/Original Ratio

0.17

Quote/RT Ratio

Posting Rhythm

Consistent

Regular posting cadence

72.4%

Weekday Posts

27.6%

Weekend Posts

Top Hashtags

#parkinsons (33) #parkinson (17) #neurotwitter (13) #parkinsonsdisease (6) #alzheimers (6) #deepbrainstimulation (5) #parkinsonsawarenessmonth (4) #neurology (4) #dbs (4) #dementia (3)

Most Mentioned

@fixelinstitute (41) @dbsthinktank (34) @brain1878 (32) @movedisorder (19) @jamaneuro (16) @albertoespay (16) @adammgrant (12) @leaddbs (12) @nobelprize (11) @ufhealth (10)

Want This Report as PDF?

We're building PDF export for these analytics reports. Register your interest to get early access.

Register Interest

Content Strategy Analysis

Based on 500 tweets

Content Type Distribution

Content Breakdown

Original Tweets 246 (49%)
Replies 12 (2%)
Retweets 206 (41%)
Quote Tweets 36 (7%)

What This Reveals About Their Strategy

This is a content-creator focused account that primarily shares original thoughts, ideas, and media. With original content dominating their feed, they position themselves as a source of new information rather than a curator. This strategy works well for establishing thought leadership.

The 206 retweets (41% of activity) show they also amplify content from others, which helps build relationships with other accounts and provides value to followers by surfacing relevant content.

Posting Patterns & Optimal Timing

Based on 500 tweets

Engagement by Hour (UTC)

Posting Frequency Over Time

Timing Insights

Understanding when an account posts and when their audience is most responsive provides valuable competitive intelligence. The charts above show when this account's content receives the most engagement, which often correlates with when their specific audience is most active on the platform.

Peak posting times vary significantly based on an account's audience demographics, timezone distribution, and content type. Accounts with global audiences often see engagement spread across multiple time windows, while those with regional focus may have more concentrated peaks.

Audience Demographics

Based on 22,621 followers

His audience includes medical professionals, patients, and the general public interested in neurological health. The content is tailored to be educational and engaging for both laypeople and experts.

Good

Audience Quality

17.9%

Suspicion Index

16.9%

Low-Quality %

141

Median Reach

Audience Quality Signals

Lower percentages indicate healthier, more authentic followers.

24.1%

Empty Bio

15.8%

<10 Tweets

20.5%

Mass Following (>2K)

0.0%

New (<90 days)

30.9%

Low Ratio (<0.1)

0.0%

New (<180 days)

75.1%

No URL

9.7%

<3 Tweets

Free Mode Analysis: These quality metrics use heuristic signals (empty bios, low tweets, suspicious ratios). For ML-powered bot detection with 95%+ accuracy, use our dedicated tool.

Try Bot Detector

Follower Reach & Influence

This account's followers have their own audiences, creating potential for secondary amplification.

67,154,745

Total Potential Reach

141

Median Follower Reach

480

75th Percentile Reach

13.8%

>1K followers

2.3%

>10K followers

0.9%

>50K followers

0.6%

>100K followers

Creator vs Consumer Split

Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).

63.7%

Creators

14,410 accounts

20.5%

Consumers

4,642 accounts

15.8%

Dormant

3,569 accounts

350

Verified Followers

1.55% of total

17.8%

Professional Bios

founder, dev, analyst, etc.

0.22

Median Follow Ratio

follower/following

Follower Influence Distribution

How many followers do their followers have?

Follower Account Age

How long have followers been on Twitter?

Geographic Distribution

Top locations where followers are based (from those who share location data):

Gainesville, FL (259) London, England (153) Boston, MA (149) United States (138) India (115) New York, NY (104) Chicago, IL (87) Toronto, Ontario (85) Philadelphia, PA (83) Florida, USA (81)

350

Verified Followers

1.55% of total

1,976

Protected Accounts

8.74% of total

7 years

Avg Account Age

of their followers

Notable Followers (By Influence)

Top accounts following this user, sorted by their follower count:

Username Followers Profession Interests
@SiriouslySusan 1,778,372 Voice Actor Voice acting, singing, speaking
@MurrayNewlands 1,520,902 Contributor pop art, art, entrepreneurship
@CynthiaLIVE 1,426,105 Entrepreneur Personal Branding, Keynote Speaking, Columnist
@SinghLions 1,335,681 Restaurateur Food, Travel, Influencer
@LollyDaskal 1,233,962 Leadership Expert -
@greggrunberg 1,192,070 Actor ACTOR, WRITER, BANDS
@JackPhan 1,113,140 Entrepreneur Visionary, Startup Entrepreneur, AdobeInsider
@AskAaronLee 1,004,393 Regional Manager Social media, Cappuccino, Introvert
@iPragmatico 973,340 Influencer Rock, Twitter, Amor
@machavelli7 931,316 Author Philosophy, History, Travel

Top Keywords in Follower Bios

neurology (1,065) research (994) parkinsons (959) medical (924) student (907) phd (886) neurologist (884) health (791) university (784) medicine (695)

Top Hashtags in Follower Bios

#medtwitter (115) #meded (93) #parkinsons (93) #neuroscience (74) #neurology (72) #neurotwitter (69) #parkinson (54) #ai (36) #stroke (35) #epilepsy (33)

17,170

Followers With Bio

5,451

Followers Without Bio

75.9%

% With Bio

24.1%

% Without Bio

Why Audience Demographics Matter

Understanding who follows an account reveals the type of influence they hold. Accounts followed primarily by users with few followers indicate broad, mainstream appeal. Those with many high-follower followers have greater potential for content amplification through secondary sharing.

Account age distribution also tells a story: a follower base with many new accounts might indicate recent viral growth, while established followers suggest long-term, stable influence. Geographic data helps understand the cultural context and timezone spread of the audience.

Buy Follower Data

Export full follower list with profile details, bios, locations, and follower counts as CSV.

Buy Followers - from $15

Buy Tweet Data

Export tweets with engagement metrics, timestamps, media, and reply/retweet details as CSV.

Buy Tweets - from $15

Viral Tweets

Top 5 by likes+RTs from 500 analyzed

14,595

Combined Engagement

0

Total Likes

14,595

Total Retweets

2,919

Avg per Tweet

Key Metrics for Viral Tweets

0%

With Media

0%

With Hashtags

100%

With @Mentions

0%

With Links

Topical Analysis:

Neurology Brain Tumors Memory Loss Dementia Medical Education Public Health

Key Insights & Takeaways

He frequently addresses confusion between medical terms like delirium and dementia, highlighting the importance of accurate terminology. He raises awareness about brain tumors, particularly glioblastoma, and its prevalence. He emphasizes the need for public understanding of neurological conditions and their implications.

Strengths

  • + Established follower base of 33,400
  • + Strong original content creation
  • + Active presence with consistent posting

Opportunities

  • ~ Optimize posting times for peak engagement windows
  • ~ Analyze top-performing content for replicable patterns
  • ~ Leverage geographic concentration for targeted content
  • ~ Explore collaboration potential with followed accounts

Summary

This analysis of @MichaelOkun reveals an growing Twitter presence with 33,400 followers. The account demonstrates a content-creator strategy, averaging 66.8 engagements per tweet. Key strengths include consistent posting and an engaged audience, with opportunities to further optimize timing and content strategy based on the patterns identified in this report.

Need Programmatic Access?

We're building an API for developers and researchers. Get access to Twitter data programmatically for your applications and analysis.

Register Interest for API Access

About This Analysis: This analysis is based on a snapshot of followers, following, and recent tweets. It evaluates structure, quality, and behavior, not historical growth. Metrics like growth rate, momentum, churn, or spike analysis require time-series data which is not available from a single snapshot.

Data collected and analyzed by twtData | Analysis date: Dec 16, 2025