Predicting Video Comment Counts Using a Hybrid Statistical and Machine-Learning Framework

Hybrid Negative Binomial regression and tree-based ML framework applied to real YouTube data; view count dominates comment counts, and a data-quality defect is identified and documented.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-14
DOI
https://doi.org/10.5281/zenodo.22749708
Primary Topic
Sentiment Analysis and Opinion Mining
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
preprint

Predicting Video Comment Counts Using a Hybrid Statistical and Machine-Learning Framework

Amirhossein MoradiSizkouhi
Zenodo (CERN European Organization for Nuclear Research)
Sentiment Analysis and Opinion Mining
preprint

Predicting Video Comment Counts Using a Hybrid Statistical and Machine-Learning Framework

Amirhossein MoradiSizkouhi
preprint en

Abstract

Hybrid Negative Binomial regression and tree-based ML framework applied to real YouTube data; view count dominates comment counts, and a data-quality defect is identified and documented.

Zenodo (CERN European Organization for Nuclear Research)
Imam Khomeini International University (IR)
Sentiment Analysis and Opinion Mining
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Predicting Video Comment Counts Using a Hybrid Statistical and Machine-Learning Framework — Amirhossein MoradiSizkouhi · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS