Jefferson County

Key demographics – Jefferson County, West Virginia

Population size

• 57,701 (2020 Census decennial count)

Age (ACS 2018–2022 5-year)

• Median age: ~40 years
• Under 18: ~22%
• 65 and over: ~17%

Gender (ACS 2018–2022 5-year)

• Female: ~51%
• Male: ~49%

Racial/ethnic composition (ACS 2018–2022 5-year)

• White, non-Hispanic: ~76%
• Black or African American, non-Hispanic: ~8–9%
• Hispanic or Latino (any race): ~7%
• Two or more races, non-Hispanic: ~6%
• Asian, non-Hispanic: ~2%
• American Indian/Alaska Native, Native Hawaiian/Other Pacific Islander, and other, non-Hispanic: <1%

Household data (ACS 2018–2022 5-year)

• Households: ~22,000
• Average household size: ~2.5–2.6
• Family households: ~68%
• Owner-occupied housing: ~75%
• Median household income: roughly low-$90,000s
• Persons in poverty: ~9%

Sources: U.S. Census Bureau, 2020 Census; American Community Survey 2018–2022 5-year estimates.

• Scope: Jefferson County, WV (2020 Census population 57,701; adults ≈ 77%).

• Estimated email users: 43,000–45,000 residents. Method: adult population (~44,000) × ~92% U.S. adult email adoption (Pew) plus most teens (school-driven usage).

• Age distribution (usage rates, applied locally):

  • 18–29: ~96% use email; near-universal among college and early-career adults.
  • 30–49: ~95%; heaviest daily use for work/parenting.
  • 50–64: ~92%; strong adoption with increasing mobile access.
  • 65+: ~85%; majority use email, though less frequently than younger cohorts.

• Gender split: Population is roughly even with a slight female majority (~51% female). Email usage shows parity by gender, so users are split ~51% female, ~49% male.

• Digital access trends:

  • Internet subscription is high for West Virginia, with about 9 in 10 households connected; fixed broadband (25/3 Mbps+) is available to the vast majority of addresses, with cable/fiber concentrated in Charles Town, Ranson, and Shepherdstown and mixed DSL/fixed-wireless in rural pockets.
  • Remote work and schooling have sustained higher daily email reliance since 2020.
  • Public libraries and Shepherd University expand free Wi‑Fi access.

• Local density/connectivity: Approximately 270 people per square mile—among the state’s densest counties—supports stronger broadband investment and consistent email access.

Jefferson County, WV mobile usage summary (2025)

Key numbers at a glance

• 2024–25 population (Census-based estimate): ~60,000; households: ~24,000–25,000
• Unique mobile users: ~49,000 residents (≈82% of total population; ≈97% of adults and ≈90% of teens 13–17)
• Smartphone users: 44,000 (≈90% of adult mobile users), notably higher than WV statewide (80–83%)
• 5G‑capable smartphones in use: ~31,000 (≈70% of smartphones), higher than WV average due to faster device refresh and stronger mid‑band 5G availability
• Active cellular lines (phones, tablets, watches, hotspots): ~60,000 (≈1.2 lines per adult mobile user), reflecting work phones and wearables among commuters
• Plan mix: ~80% postpaid, ~20% prepaid/MVNO; postpaid share is materially higher than statewide WV (≈65–70%)
• Wireless‑only households (no landline): ~76% versus WV ≈67%, in line with national suburban norms

What differentiates Jefferson County from the rest of West Virginia

• Demographics that drive higher adoption and faster refresh cycles: lower median age, higher median income, and higher college attainment than the state average. These factors correlate with:
  • Higher smartphone and 5G device penetration
  • More unlimited 5G plans and multi‑line family accounts
  • Greater use of iOS devices and wearables (no exact split provided, but skew more “national/suburban” than WV statewide)
• Commuter and tourism effects: weekday out‑commuting to the DC metro and weekend tourism (Harpers Ferry, Shepherdstown, Hollywood Casino) produce pronounced time‑of‑day and weekend congestion spikes uncommon in most WV counties.
• Network quality: contiguous 5G mid‑band along the WV‑9 and US‑340 corridors puts day‑to‑day mobile performance notably above the WV average, which still has large LTE‑only or fringe areas in rural counties.

Demographic breakdown and usage patterns

• Age: A larger share of 25–49 vs. WV average supports above‑average smartphone and 5G adoption; teens’ device ownership is near national suburban levels (~90%+ with a phone).
• Income/education: Median household income is significantly above WV’s statewide median, and bachelor’s attainment is higher; this aligns with higher postpaid take‑up, premium device mix, and greater accessory/wearable penetration.
• Household mix: More dual‑income, commuting households drives multi‑line family plans, hotspot add‑ons for travel, and greater reliance on mobile navigation and payments.
• Line density: Work‑issued phones among federal and private‑sector commuters push the lines‑per‑adult ratio to roughly 1.2, above WV’s statewide average.

Digital infrastructure and coverage

• 5G footprint
  • T‑Mobile: robust mid‑band (n41) 5G along Charles Town–Ranson–Shepherdstown, WV‑9 to Loudoun County, and US‑340 toward Harpers Ferry and Bolivar.
  • Verizon: C‑band (n77) 5G across primary population centers and corridors; strong LTE fallback in rural pockets.
  • AT&T: 5G/5G+ present in town centers and along main corridors; FirstNet supports public safety with prioritized access.
  • Net effect: Most populated areas have 5G from at least one carrier; multi‑carrier 5G overlap is common in towns—well above WV’s statewide average.
• Capacity and congestion
  • Known peak‑load zones: Hollywood Casino/Charles Town Races events, Shepherd University game days and festivals, Harpers Ferry weekends/holidays. Temporary slowdowns reflect sector loading rather than coverage gaps.
• Terrain and edge cases
  • Ridge‑and‑valley topography creates dead zones in Blue Ridge foothills, parts of Harpers Ferry National Historical Park, and low‑lying farmland between Kearneysville and Shenandoah Junction. In‑building coverage can soften in older stone/brick structures in Shepherdstown and Harpers Ferry.
  • Cross‑border handoffs to MD/VA sites are common near the Potomac and along US‑340; most modern devices manage seamless switching, but it can affect emergency call routing if Wi‑Fi calling is disabled.
• Backhaul and fiber
  • Multiple fiber providers have built out along WV‑9/US‑340 and town grids (e.g., Frontier Fiber expansions; Glo Fiber/Shentel builds; business fiber from regional carriers). This backhaul underpins 5G capacity and small‑cell infill in Charles Town, Ranson, and Shepherdstown.
• Fixed wireless home internet (FWA)
  • T‑Mobile Home Internet and Verizon 5G Home are widely offered in and around town centers; adoption is strong for renters and new movers. Estimated household share ~8–12%, higher than most WV counties where mid‑band 5G is spottier.

Comparisons to WV statewide trends

• Coverage: Jefferson’s populated corridors have multi‑carrier 5G; many WV counties still rely largely on LTE with patchy mid‑band 5G.
• Adoption: Smartphone and 5G device penetration, postpaid share, and wearable attachment rates are all higher in Jefferson than the state average.
• Reliance on wireless: Wireless‑only households and day‑to‑day dependence on mobile data for work commuting and tourism are higher than statewide norms.
• Network performance: Faster median downlink speeds are typical due to denser sites, fresher spectrum deployments (C‑band and 2.5 GHz), and stronger fiber backhaul.

Estimated user counts (2025)

• Adults (18+): ~46,000–47,000; adult mobile ownership ≈97% ⇒ ~46,000 adult mobile users
• Teens (13–17): ~3,500–3,700; phone ownership ≈90–95% ⇒ ~3,300 teen mobile users
• Total unique mobile users: ~49,000
• Smartphone users: ~44,000
• 5G‑capable smartphones: ~31,000
• Active lines (phones, tablets, watches, hotspots): ~60,000

Implications

• Capacity planning should prioritize weekend/tourism nodes and event venues, plus small‑cell or sector splits along US‑340 and WV‑9.
• Given strong fiber backhaul, continued mid‑band 5G densification will yield outsized performance gains versus other WV counties.
• MVNO opportunity exists but the market is skewed to postpaid; device financing and bundled perks are more effective than deep‑discount prepaid in this county.
• FWA can keep gaining share in town centers and new subdivisions; however, in fringe terrain pockets, macro densification or targeted fixed wireless beams are still needed to stabilize evening speeds.

Method notes

• Population, household counts, and demographic characteristics are based on recent Census/ACS trajectories; usage and device estimates are modeled from national adoption rates adjusted for Jefferson County’s younger, higher‑income profile and observed 5G availability in the Eastern Panhandle. Where county‑specific counts are not published, figures are stated as best‑available 2024–25 estimates.

Social media usage in Jefferson County, West Virginia — concise snapshot (2025)

Overview and user stats

• Population context: 2020 Census counted 57,701 residents; the county has grown since and skews slightly female (~51%). Household broadband access is high for WV (mid–high 80% per recent ACS), supporting broad social use.
• Overall penetration: In line with national patterns, roughly 8 in 10 adults in the county use at least one major social platform daily or weekly.

Most-used platforms (share of adults; best-available estimates grounded in latest Pew Research adoption rates)

• YouTube: 80–85%
• Facebook: 65–70%
• Instagram: 45–50%
• Pinterest: 30–35%
• TikTok: 30–35%
• Snapchat: 25–30%
• LinkedIn: 25–30%
• X (Twitter): 20–25%
• Reddit: 20–25%
• WhatsApp: 20–25%
• Nextdoor: 15–20%

Age-group patterns

• 18–29: Instagram, TikTok, Snapchat lead; YouTube near-universal; Facebook used for events, Marketplace, and local groups more than posting to the feed.
• 30–49: Facebook and YouTube dominate daily use; Instagram growing; LinkedIn usage elevated due to DC/NOVA commuters; WhatsApp/Group chats common for family, youth sports.
• 50–64: Facebook is primary; YouTube strong for DIY and news; Pinterest usage notable; gradual adoption of TikTok/short-form video.
• 65+: Facebook remains the hub for community info; YouTube for tutorials and local/government briefings; Nextdoor adoption present in HOA/neighborhood contexts.

Gender breakdown

• Women: Higher use of Facebook, Instagram, Pinterest, and TikTok; heavy participation in local Facebook Groups (schools, youth sports, buy/sell, community events).
• Men: Higher use of YouTube, Reddit, X, and LinkedIn; strong engagement with how-to/auto/home projects on YouTube and local news/politics threads.

Behavioral trends

• Facebook Groups = civic backbone: Central for Jefferson County Schools updates, youth sports, local government/commission news, traffic/commuter alerts (US‑340/SR‑9), weather/flooding, and community marketplaces in Charles Town, Ranson, Shepherdstown, Bolivar–Harpers Ferry.
• Short‑form video growth: Local businesses, realtors, and tourism operators use Instagram Reels/TikTok to showcase Harpers Ferry attractions, dining, breweries, and events; cross-posting to Facebook is routine.
• Neighborhood forums: Nextdoor used for HOA notices, contractor referrals, and safety posts in suburban developments; engagement spikes with service outages or public-works issues.
• Commerce and services: Facebook Marketplace is the default for secondhand goods; service providers (home, auto, pet care) rely on Facebook Pages, local Groups, and Instagram Stories for bookings and referrals.
• News and alerts: County agencies, law enforcement, and nearby media push updates via Facebook and YouTube; posts about schools, road closures, and public safety see high share rates.
• Messaging over feeds: FB Messenger and WhatsApp groups coordinate families, carpooling, and activities; Snapchat remains a primary messaging channel for teens/young adults.

Notes on figures

• Platform percentages reflect the latest publicly reported U.S. adult adoption rates (Pew Research Center, 2024) applied to Jefferson County’s demographic profile; they align with observed suburban/rural usage patterns and local infrastructure (broadband/smartphone access).
• Where direct county-level platform stats are not published, ranges are provided to give a reliable, decision-ready view of relative platform reach and demographic skew.