📄

Paper

Sentiment analysis through twitter as a mechanism for assessing university satisfaction

by Independent / Community 0082fb8f738cdc765d8683178322a159eeb0f07b

Free2AITools Nexus Index

65.6

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 76

P: Popularity 51

R: Recency 100

Q: Quality 65

Tech Context

Vital Performance —

Currently, the data generated in the university environment related to the perception of satisfaction is generated through surveys with categorical response questions defined on a Likert scale, with factors already defined to be evaluated, applied once per academic semester, which generates very biased information. This leads us to wonder why this survey is applied only once and why it only asks about some factors. The objective of the article is to demonstrate the feasibility of a proposal t...

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Semantic Scholar 10 Citations

Paper Information Summary
Entity Passport
Registry ID	0082fb8f738cdc765d8683178322a159eeb0f07b
License	ArXiv
Provider	semantic_scholar

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Cite this paper

Academic & Research Attribution

BibTeX

@misc{0082fb8f738cdc765d8683178322a159eeb0f07b,
  author = {Unknown},
  title = {Sentiment analysis through twitter as a mechanism for assessing university satisfaction Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/0082fb8f738cdc765d8683178322a159eeb0f07b}},
  note = {Accessed via Free2AITools.}
}

APA Style

Unknown. (2026). Sentiment analysis through twitter as a mechanism for assessing university satisfaction [Paper]. Free2AITools. https://api.semanticscholar.org/0082fb8f738cdc765d8683178322a159eeb0f07b

🔬Technical Deep Dive

Full Specifications [+]

⚖️ Free2AITools Nexus Index V2.0

Methodology How FNI works

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 76

Popularity (P) 51

Recency (R) 100

Quality (Q) 65

💬 Index Insight

FNI V2.0 for Sentiment analysis through twitter as a mechanism for assessing university satisfaction: Authority (A:76), Popularity (P:51), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology

Open data Updated: Live data

📝 Executive Summary

"Currently, the data generated in the university environment related to the perception of satisfaction is generated through surveys with categorical response questions defined on a Likert scale, with factors already defined to be evaluated, applied once per academic semester, which generates very biased information. This leads us to wonder why this survey is applied only once and why it only asks about some factors. The objective of the article is to demonstrate the feasibility of a proposal t..."

❝ Cite Node

@article{Unknown2026Sentiment,
  title={Sentiment analysis through twitter as a mechanism for assessing university satisfaction},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

🔗 Full Paper

Free2AITools indexes the abstract and factual metadata for this paper. Read the complete, authoritative paper on the official source.

Read the full paper on arXiv

📊 Research Signals

📈10CitationsSemantic Scholar

🏛️76AuthorityFNI pillar

⏱️100RecencyFNI pillar

✅65QualityFNI pillar

🗂️automation workflowField

📦Data Source: semantic_scholar

🔄 Updated daily

Source summary: Based on semantic_scholar metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Paper Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

source: semantic_scholar
author: Unknown
license: ArXiv
tags: paper, research, academic

⚙️ Technical Specs

architecture: null
params billions: 7
context length: null
pipeline tag

📊 Engagement & Metrics

downloads: 0
stars: null
forks: null
citations: 10

Data indexed from public sources. Updated daily.