The document outlines the efforts of the Florida Digital Humanities Consortium to analyze voter participation in Florida, focusing on data preparation and analysis of voter registration and turnout. It details the profiles created based on voter behavior from 2012 to 2020, including recommendations for increasing participation among recently inactive voters, particularly targeting younger demographics. Collaboration with the League of Women Voters and the contributions of university faculty and interns are highlighted in the initiative to enhance data-driven decision-making for public sector and nonprofit organizations.

1. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
1
Profiling Florida Voter Participation

2. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
2
FL-DSSG Team
Program Directors
Dr. Dan Richard
Associate Professor of Psychology,
University of North Florida (UNF)
Dr. Karthikeyan Umapathy
Associate Professor of Computing,
Distinguished FIS Professor,
University of North Florida (UNF)
Interns
Payal Agarwal
Computer Science,
Master of Science,
UNF
Thomas Hunt
Mathematical Science - Statistics,
Master of Science Student,
UNF
Joyner Johnson
Computing and Information Sciences
Master of Science Student,
UNF
Community Partner
Leah Nash
Executive Director,
League of Women Voters of Florida

3. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
3
FIS Computing Distinguished Professorship Award
Jaguars Foundation
Special thanks to DSSG Faculty and Industry
mentors for guiding interns with solving
technical and domain problems.

4. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
4
Gaining actionable
insights from data
Helping Public Sector
and Nonprofit
Organizations make
data-driven decisions
Training data scientists
with social conscious
Florida Data Science for Social Good (FL-DSSG)
“Social Trustees of
Knowledge”

5. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
5
Summer
internship
program open to
all UNF students
(undergraduate
and graduate)
Social Sciences:
15
UNF: 28
Masters: 24
Duval: 14
Nassau: 2
Orange: 1
Palm Beach: 1
38 18
2017
Florida Data
Science for Social
Good
(FL-DSSG)

6. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
6
League of Women Voters - Florida
1939
Florida League
founded
Florida chapters
29
1920
LWV-US founded ~
6 months before
the passage of the
19th Amendment
Nonpartisan: No political party affiliation
Increasing “participation in government” plus education on public issues

7. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
7
From Wicked Problem
Access to voting
An important part
of participation in
government
Access to information
Transformation through
data
Maximizing impact
Prospective voters might not
know the requirements of
keeping their registration or
active status maintained
By using data, the league can
make decisions with more
complete information
With more data open to
the public, our client can
have a larger impact
to Opportunity

8. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
8
Project Focus
Voter registration and
turnout in Florida
Geographic focus on
voting
Recommendations to increase
voter registration and turnout

9. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
9
• County code
• Voter ID
Common
Items
Raw Data Source
 Data from Florida Division of Elections
 2 types of voter data
 Based on 67 county files each
Thanks to
Dr. Mike Binder
for sharing data
files
• File size – based on
population [range of file size –
~1.6M]
• Total columns – 38 [Address,
Mailing Address, Gender,
DOB, Last Registration Date,
etc]
Voter Registration
• Election info [2006 - 2020]
• File size – based on voter’s
participation in all elections
[range – ~10M]
• Total columns – 5 [Election
Type , Election Date, History
Code]
Voter History

10. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
10
Data Preparation
Voter Registration
Each county data was
cleaned to remove
unwanted variables and
extract non-identifying
variables such as Voter ID,
County Code, Zip code, Age,
Ethnicity, and Sex
Voter History
County data was sorted with
unique voter ID and filtered data
relevant to federal general
elections in 2012 – 2020.
Extracted data was cleaned to
remove duplicates and recode
misclassified vote types in same
election
Voter Registration and History
flat files for each county was
merged to prepare data files for
analysis.
67 files were generated.

11. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
11
• General elections data between 2012 – 2020
• 67 files were generated
The columns are:
Voter ID
Registration county code
Residential zip code
Sex
Ethnicity
Age
Precinct coding
District coding
[2012 … 2020] VoteType [see table]
[2012 … 2020] Vote indicator [1 or blank]
[2012 … 2020] County code
Voting History
Code
History Description
Y Voted at Polls
A Voted by Mail
E Voted Early
B Vote-by-Mail Ballot Not Counted
P Provisional Ballot Not Counted
N
Did Not Vote (did not consider by all
counties)
M Misclassified
Data Preparation
- Voter
Registration
+ Voter
History

12. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
12
Merged Metropolitan/Micropolitan and Rural
Areas
• Used Pandas framework
to combined merged
county files based on
metro and micropolitan
areas
• Total 28 metro/micro and
rural areas encompassing
the entire state
• Adjacent rural areas were
grouped as Panhandle:
Jackson - Liberty and
Panhandle: Madison -
Suwannee Sources: https://www.whitehouse.gov/wp-
content/uploads/2020/03/Bulletin-20-01.pdf

13. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
13
Voter Profile Generation
• Classifying the VoterID based on the eligibility and total vote counts on each
general election held between 2012 – 2020
Profile Code Voter Profile Description
1 Always Eligible voters participated in all general elections
2 Increasing
Eligible voters participated recent in general elections but
not in the past elections
3 Intermittent Eligible voters participated in some elections but not all
4 Decreasing
Eligible voters participated past general elections but not
recently
5 Never Voted Eligible voters didn’t participate in the elections
6 Not Eligible Registered but under 18 years of age

14. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
14
Frequency Table Voter Profile
Rural

15. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
15
Tallahassee MSA
32304
Miami-Ft. Lauderdale-
Pompano Beach MSA
33411
33311
33023
33024
33025
Orlando-Kissimmee-
Sanford MSA
34787
Tampa-St. Petersburg-
Clearwater MSA
33578
33647
34668
Metropolitan Statistical Areas – Voter Profile Analysis

16. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
16
Metropolitan Area Comparison – Boosted Tree
Orlando – Kissimmee-
Sanford
34%
16%
15%
16%
Zip Code
2018 Vote Type
Voter Status
Age
30%
14%
18%
15%
Learning Rate: 0.1
Tampa-St. Petersburg-
Clearwater
Misclassification Rate: 0.22
Learning Rate: 0.1
Misclassification Rate: 0.22
Predict:
2020 Participation
Inputs:
2012 to 2018 voter
registration and history data
40%
8%
10%
30%
Miami – Ft. Lauderdale –
Pompano Beach
Learning Rate: 0.1
Misclassification Rate: 0.23
Over 75%
Column Contributions

17. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
17
Registered Voters
Age 18 to 40
Miami – Ft. Lauderdale
– Pompano Beach MSA
33186
33157
33033
33311
33024
33025

18. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
18
Target recently inactive voters
based on voter registration
data
Conduct data collection
about local chapter
activities
Targeted campaigns for
citizens below 40 years of
age
Start chapters in
micropolitan and
rural areas of the
state
Recommendations

19. Florida Digital Humanities Consortium (FLDH) – St. Augustine,
FL
April 2, 2022
19
Thank You!