Elizabeth Doran

Reporter

AS SEEN ON

Preston's Summary

Elizabeth Doran is a reporter at Syracuse Media Group, covering schools and local government primarily in Onondaga County. Her work encompasses themes such as public education, real estate development, and local governance, showcasing her expertise in regional issues and the housing market. Elizabeth has been featured in various publications, including Olean Times Herald, Staten Island Advance/SILive.com, and NY Cannabis Insider, highlighting her impactful journalism in the community.

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

Geo Focus

Manlius, United States (Local)

Coverage Attributes:

Beta
Informative: 75 %
Interviews Q&as: 9 %
Data Driven: 8 %
Events: 6 %

Themes Covered:

Not enough data icon

Not enough data

Most Recent Topics:

  • Commercial Real Estate
  • Housing Market
  • Real Estate Development
  • Public Education
  • School Districts

Pitching Insights

Elizabeth Doran's coverage revolves around local news, with a focus on education, government & politics. She regularly reports on school district developments, local crime incidents, municipal decisions and community events in the Syracuse area.

To effectively reach out to Elizabeth for potential coverage or sources related to her areas of interest, consider pitching stories involving local educational initiatives or policies, political developments within Onondaga County or Syracuse city, and business updates impacting the region. Additionally, breaking news tips regarding significant occurrences in these areas may also pique her interest.

Given her emphasis on local matters like school test scores and district-specific topics such as appointments and fines imposed by municipalities within Onondaga County, she is likely interested in pitches that are directly relevant to this geographic scope.

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

Journalists With Similar Coverage:

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