Roger Clark

Reporter, Anchor, Spectrum News NY1

Preston's Summary

Roger Clark is a reporter and anchor for Spectrum News NY1, focusing on local news in New York City. With a passion for storytelling, Roger covers a wide range of topics including arts and culture, community events, and local traditions. His work has been featured in various publications and news outlets, showcasing his dedication to keeping New Yorkers informed and engaged with their city.

Preston is the artificial intelligence that powers the Intelligent Relations PR platform. Meet Preston

Geo Focus

New York, United States (Local)

Coverage Attributes:

Beta
Event Coverage: 57 %
Seasonal: 16 %
Profile Feature: 9 %
Promotional Deal: 5 %
Private Sector Announcements: 3 %

Themes Covered:

Not enough data icon

Not enough data

Most Recent Topics:

  • Art Dealing
  • Urban Art & Street Art
  • Plays & Musicals
  • Graphic Design
  • Fine Art
  • Home & Garden

Pitching Insights

Roger Clark's journalistic coverage is heavily focused on local events, seasonal traditions, and cultural aspects of New York City. He seems to have a keen interest in covering unique local events, artistic displays, and traditional celebrations within the city.

Given Roger's focus on local entertainment news and cultural themes related to New York City boroughs such as the Bronx, he may be interested in pitches that highlight lesser-known but impactful community-driven initiatives or upcoming events within these areas. Additionally, stories centered around art exhibitions or performances with ties to New York City’s diverse culture might capture his attention.

Since Roger primarily covers local events and seasonal traditions in New York City boroughs like The Bronx, reaching out with human-interest stories about individuals or communities engaging in creative expressions of holiday traditions could resonate well with him.

This information evolves through artificial intelligence and human feedback. Improve this profile .

Journalists With Similar Coverage:

Based on similarity of content.
Publications
Most recent topics
Not enough data
Publications
Most recent topics
Not enough data
Most recent topics
Not enough data
Most recent topics
Not enough data
Most recent topics
Not enough data