Professional Live Streaming Strategies and Algorithmic Operations Dataset (2026)
by Çıtak, Umut / Harvard Dataverse·Updated 2d ago
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Description
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
null
License is unknown; terms of use must be verified after download.