Professional Live Streaming Strategies and Algorithmic Operations Dataset (2026)

Umut Çıtak's dataset from Harvard Dataverse, updated June 2026, contains strategic, psychological, and technical operational data extracted from the 'Professional Live Streaming Guide: Algorithmic Strategies and Audience Psychology' research. It is structured to analyze viewer retention, algorithmic discoverability, and content monetization. The dataset is divided into two main parts covering platform algorithms, neuro-marketing, technical setups, crisis management, AI tool integration, and SEO strategies.

Use Cases

• Analyzing viewer retention patterns based on strategic and psychological data mentioned in the description
• Modeling algorithmic discoverability for live streams based on platform algorithm and SEO strategy data
• Investigating content monetization strategies based on operational and technical setup data
• Studying crisis management and career sustainability in live streaming based on the described sections

Strengths

• Data is structured into two distinct thematic parts (Sections 1-15 and 16-31) covering a wide range of operational topics
• Dataset is sourced from a specific, named research guide ('Professional Live Streaming Guide: Algorithmic Strategies and Audience Psychology')
• Last updated date is precisely recorded as 2026-06-04 14:29:57

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count, file formats, and sample data are unknown, which may limit suitability assessment

Provenance

Source

Harvard Dataverse, author Çıtak, Umut

Collection Method

Extracted from the 'Professional Live Streaming Guide: Algorithmic Strategies and Audience Psychology' research

Time Range

2026

Freshness

Last updated 2026-06-04 14:29:57; freshness should be verified

Geography

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