Cabell County

Key demographics – Cabell County, West Virginia (latest available)

• Population (2023 estimate): ~94,000
• Age:
  • Median age: ~39
  • Under 18: ~19%
  • 65 and over: ~19%
• Gender: ~52% female, ~48% male
• Race (race alone, percent of total):
  • White: ~89%
  • Black or African American: ~5%
  • Asian: ~2%
  • American Indian/Alaska Native: ~0.2%
  • Native Hawaiian/Other Pacific Islander: ~0.1%
  • Some other race: ~0.4%
  • Two or more races: ~3–4%
• Ethnicity:
  • Hispanic/Latino (of any race): ~2%
• Households (2019–2023 period):
  • Total households: ~40,000
  • Average household size: ~2.2
  • Family households: ~54% (married-couple families ~36%)
  • Nonfamily households: ~46%
  • Households with children under 18: ~23%
  • Households with one person living alone: ~38% (about 12% age 65+ living alone)

Source: U.S. Census Bureau, American Community Survey 2019–2023 5-year estimates; Population Estimates Program, Vintage 2023. Figures are estimates and rounded for readability.

Cabell County, WV snapshot (estimates)

• Population: ≈94,000.
• Email users: 72,000–80,000 residents (about 77–85% use email at least monthly), reflecting WV internet adoption and Cabell’s urban core.
• Age pattern (adoption among each group; share of email users in parentheses):
  • 18–34: 95–99% (≈30–35%)
  • 35–54: 95–98% (≈30–35%)
  • 55–64: 90–95% (≈15–18%)
  • 65+: 75–85% (≈15–20%)
• Gender split: roughly even; slight female majority (~51–52%) among users, mirroring the population.

Digital access trends

• Household broadband: roughly 80–85% countywide; 15–20% are smartphone‑only internet users.
• Technology mix: Cable and growing fiber coverage in Huntington/Barboursville; DSL and fixed‑wireless more common toward rural edges.
• Affordability: Above‑average participation in the Affordable Connectivity Program for WV; strong public access via Marshall University, libraries, and health systems.

Local density/connectivity facts

• The Huntington urban core is one of WV’s denser areas, supporting multiple ISPs and higher advertised speeds; outlying hollows have fewer providers and lower adoption.
• Overall email usage is higher in city ZIP codes, tracking better broadband availability and campus-driven connectivity.

Notes: Figures are synthesized from Census population and state/national internet/email usage patterns.

Cabell County, WV: Mobile phone usage snapshot (with county-specific estimates and how it differs from the state)

Headline estimates

• Total residents regularly using a mobile phone (any type): roughly 75,000–80,000 people.
  • Basis: county population around mid-90,000s; about 74,000 adults plus ~5,000–6,000 teens 13–17, with 92–97% adult mobile ownership and ~95% teen ownership (Pew Research norms, adjusted for a more urban/student county).
• Adult smartphone users: about 64,000–67,000; including teens, total smartphone users around 69,000–72,000.
  • Cabell’s smartphone adoption is likely a few points higher than the West Virginia average (Cabell ≈ 86–90% of adults vs statewide ≈ 80–84%), driven by Huntington’s urban core and Marshall University’s student population.

What’s different from the statewide picture

• Higher adoption and usage intensity: Cabell’s younger, more urban profile and student presence nudge smartphone ownership and app-based services (mobile banking, food delivery, ride-hail) above WV averages.
• Better 5G availability and speeds in the urban corridor: Huntington/Barboursville have broader mid-band 5G than many WV counties, with typical urban 5G speeds in the low hundreds of Mbps; rural WV often remains LTE/low-band 5G with lower throughput.
• More prepaid/MVNO presence: Student and lower-income renter segments in Huntington likely raise prepaid share a few points above the state average, alongside strong postpaid family-plan penetration in suburbs.
• Higher uptake of 5G fixed wireless for home internet: Where mid-band 5G is strong, Cabell households show greater adoption of mobile-based home internet than much of WV, substituting for or supplementing cable/DSL.

Demographic breakdown (county tendencies vs WV)

• Age
  • 18–29: Very high smartphone ownership (≈95–98%). Cabell’s large student cohort pushes this group’s share above the WV average, lifting overall penetration.
  • 30–49: High ownership (≈93–96%), comparable to state but with heavier data/app use.
  • 50–64: Solid ownership (≈83–90%), roughly on par with WV; suburban users more likely on 5G-capable devices than peers in rural counties.
  • 65+: Ownership substantially lower (≈60–70%), but slightly higher than WV’s overall senior rate due to better device availability/support and healthcare apps tied to local hospitals.
• Income and housing
  • Lower-income renters in Huntington have high smartphone reliance and above-average “smartphone-only” internet use (mobile data instead of fixed broadband). In rural WV, smartphone-only is often driven by lack of fixed options; in Cabell it’s more often a cost/tenure choice among students and renters.
  • Suburban homeowners (Barboursville, Milton) skew toward postpaid family plans and newer 5G handsets.
• Race/ethnicity
  • Cabell is less diverse than the U.S. average; mobile adoption gaps by race/ethnicity are smaller in absolute numbers than in large metros. Within Cabell, differences in mobile reliance track more with income and age than race.

Digital infrastructure highlights

• Coverage and capacity
  • All three national carriers operate along the I‑64/US‑60 corridor, with dense macro coverage in Huntington and along major roads. Mid-band 5G is broadly available in the urban core; many outlying and hilly areas remain LTE/low-band 5G.
  • Expected performance: urban/suburban mid-band 5G often 150–400 Mbps; LTE-only or fringe 5G in hollows/valleys often 5–30 Mbps, with signal variability from terrain.
  • Event-driven loads: campus and stadium areas can see temporary congestion during games and festivals, mitigated where small cells or venue systems are present.
• Terrain-related gaps
  • Coverage challenges persist in parts of the county away from the river valley and I‑64—particularly in wooded hollows and along secondary roads—though these gaps are smaller and less persistent than in many rural WV counties.
• Backhaul and fiber
  • The I‑64 corridor has comparatively good fiber backhaul supporting 5G; this underpins better capacity than large parts of the state. Outside the corridor, fewer fiber routes can constrain upgrade pace.
• Public safety and institutions
  • County public safety benefits from statewide FirstNet build-outs and generally stronger carrier overlap than rural WV counties. Hospitals and campus buildings typically have enhanced in-building solutions and robust Wi‑Fi, offloading mobile traffic.

Behavioral and plan trends

• Cabell shows:
  • Higher smartphone upgrade cadence (students and commuters).
  • Stronger adoption of mobile payments, telehealth, and two-factor authentication tied to university and hospital ecosystems.
  • A mixed plan market: postpaid family plans in suburbs; prepaid/MVNO among students and service workers; business lines tied to healthcare and logistics.

Method notes and uncertainty

• Estimates combine: U.S. Census/ACS county population and age structure, Pew Research Center mobile/smartphone ownership rates by age/urbanicity (2023–2024), and FCC/carrier-reported coverage patterns as of 2024. County-level ownership is inferred by applying demographic-weighted national/rural rates and adjusting for Cabell’s urban/student profile. Use ranges rather than point values due to limited direct county surveys.

Here’s a concise, data‑informed snapshot for Cabell County, WV (Huntington/Barboursville area). Figures are estimates based on county demographics and U.S. social media patterns (Pew Research, platform audience tools), adjusted for the local university presence.

User stats

• Population: ~94,000 residents.
• Estimated active social media users: 59,000–65,000 total (includes ~54,000–59,000 adults and ~5,500–6,000 teens 13–17).
• Device mix: Predominantly mobile; desktop use concentrated in work hours.

Age mix among social users (share of local social users)

• 13–17: ~9%
• 18–24: ~19% (boosted by Marshall University)
• 25–34: ~19%
• 35–44: ~15%
• 45–54: ~13%
• 55–64: ~12%
• 65+: ~13%

Gender breakdown (share of local social users)

• Female: ~52–54%
• Male: ~46–48%
• Nonbinary/other: small but present (no reliable local %)

Most‑used platforms (share of local social users; overlapping)

• YouTube: ~78–85%
• Facebook: ~65–72% (very strong for groups/events/Marketplace)
• Instagram: ~45–55%
• TikTok: ~40–50% (skews 13–34)
• Snapchat: ~35–45% (heavy among high school/college)
• Pinterest: ~28–35% (skews female, DIY/home/food)
• LinkedIn: ~18–25% (healthcare, education, government)
• X/Twitter: ~15–22% (news/sports, esp. Marshall)
• Reddit: ~12–18% (younger, tech/gaming/local subs)
• Note: Among Facebook users, ~75–85% engage with Groups/Marketplace monthly.

Behavioral trends to know

• Content that travels: local weather alerts, school/road closures, Marshall athletics, high‑school sports, community events (festivals, fairs), restaurant openings/deals, lost/found pets, local philanthropy.
• Video first: Short, vertical video (Reels/TikTok, <30–45s) drives reach; YouTube used for how‑tos, highlights, and local news segments.
• Discovery paths:
  • Under 35: Instagram Stories/Reels and TikTok for events and venues; Snapchat for friends/campus life.
  • 35+: Facebook Groups/Events for community info; Marketplace for buying/selling.
• Engagement windows: Evenings (7–10 pm) strongest across platforms; lunchtime bump (11:30 am–1 pm). Facebook also performs on weekend mornings; TikTok late evenings.
• Messaging behavior: High response via Facebook Messenger and Instagram DMs for customer service; phone calls less preferred after business hours.
• Commerce/jobs: Facebook Groups/Marketplace and local pages drive micro‑commerce and job leads (notably healthcare, retail, logistics).
• Local niches: Healthcare and education fuel LinkedIn engagement; sports/news accounts anchor X/Twitter activity.
• Access considerations: Strong mobile usage; connectivity drops outside the urban core—optimize for fast, captioned, mobile‑friendly content.

Notes and caveats

• Exact county‑level platform counts aren’t publicly reported; figures are inferred from national adoption rates, platform mix by age, county age/sex distribution, and the university effect. Use ranges for planning and validate with your own page insights/ad reach where possible.