Data Frames: Factors Influencing Data Journalism Adoption in Israeli Newsrooms

Tamar Ashuri's study analyzes the adoption of data journalism practices (DJP) within news organizations. The research is based on 27 in-depth interviews conducted in a major Israeli news organization, introducing a 'data frame' analytical model. The dataset was last updated on 2026-06-02.

Use Cases

• Analyzing cognitive barriers to technology adoption based on the 'data frame' framework
• Studying professional role friction in news organizations based on interview data from reporters, editors, and managers
• Modeling organizational sense-making processes based on themes of perceived value, relevance, and feasibility

Strengths

• Introduces a novel analytical model ('data frame' framework) for studying technology adoption
• Based on 27 in-depth interviews providing rich qualitative insights
• Focuses on cognitive and organizational dynamics beyond conventional technical barriers

Limitations

• Dataset size is 46.6 KB, indicating a very limited scope of data
• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download

Provenance

Source

Tamar Ashuri

Collection Method

27 in-depth interviews

Freshness

Last updated 2026-06-02 21:29:43; freshness should be verified

Geography

Israel