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MVP Investment

$9K - $12K
6-10 weeks
Engineering
$8,000
Cloud Hosting
$240
SaaS Stack
$300
Domain & Legal
$100

6mo ROI

2-4x

3yr ROI

10-20x

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Talent Scout

K

Keito Inoshita

Kansai University

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Emotional experts on LinkedIn & GitHub

References (11)

[1]
The power of social networks and social media’s filter bubble in shaping polarisation: an agent-based model
2024Cristina Chueca Del Cerro
[2]
Scaling Large-Language-Model-based Multi-Agent Collaboration
2024Cheng Qian, Zihao Xie et al.
[3]
Prompt-Based Editing for Text Style Transfer
2023Guoqing Luo, Yu Tong Han et al.
[4]
The Breaking News Effect and Its Impact on the Credibility and Trust in Information Posted on Social Media
2023Corina Pelau, M. Pop et al.
[5]
Optimal nudging for cognitively bounded agents: A framework for modeling, predicting, and controlling the effects of choice architectures.
2022Frederick Callaway, M. Hardy et al.
[6]
Mining Dual Emotion for Fake News Detection
2019Xueyao Zhang, Juan Cao et al.
[7]
Delete, Retrieve, Generate: a Simple Approach to Sentiment and Style Transfer
2018Juncen Li, Robin Jia et al.
[8]
The science of fake news
2018D. Lazer, M. Baum et al.
[9]
Character-level Convolutional Networks for Text Classification
2015Xiang Zhang, J. Zhao et al.
[10]
Emotions, Partisanship, and Misperceptions: How Anger and Anxiety Moderate the Effect of Partisan Bias on Susceptibility to Political Misinformation
2015Brian E. Weeks
[11]
The Readability of Tweets and their Geographic Correlation with Education
2014J. Davenport, R. Deline

Founder's Pitch

"A multi-agent AI system for reducing excessive emotional stimulation in news consumption using language models."

Emotional AIScore: 6View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

1/4 signals

2.5

Quick Build

4/4 signals

10

Series A Potential

2/4 signals

5

Sources used for this analysis

arXiv Paper

Full-text PDF analysis of the research paper

GitHub Repository

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Why It Matters

It addresses the impact of sensational content on consumer behavior by reducing emotional stimuli in consumed information, which could promote healthier decision making in an attention-driven content market.

Product Angle

This technology could be offered as a SaaS platform or integrated directly into news aggregation services, media sites, or personal content filters, allowing consumers to control emotional exposure in their digital media consumption.

Disruption

It could replace or augment current content moderation approaches and tools used by social media and news platforms, particularly those focused on psychological health and well-being.

Product Opportunity

The market includes media organizations, content aggregators, web and social media platforms focusing on improving user experience and compliance with content moderation guidelines. Consumers and platforms looking to reduce the negative mental health impacts of sensational content could potentially pay for this service.

Use Case Idea

Create a browser plugin or application that applies MALLET's techniques to sanitize web content in real-time, offering personalized emotional detoxification for news consumers.

Science

The paper introduces a multi-agent system called MALLET utilizing BERT and LLMs to adjust the emotional tone of online content without losing factual integrity. It uses emotion analysis to gauge the emotional intensity of text and rewrites content to offer versions (BALANCED, COOL) that are more neutral in emotional impact.

Method & Eval

The system was evaluated using the AG News dataset, where it effectively reduced stimulus scores while preserving semantic integrity. Comparisons were made between different presentation modes (RAW, BALANCED, COOL) and their emotional delivery effects.

Caveats

The technology might struggle with highly sensitive topics where factual details inherently carry emotional weight, such as crisis or conflict reporting. Personalization might require significant user interaction or data which can be a privacy concern.

Author Intelligence

Keito Inoshita

LEAD
Kansai University
inosita.2865@gmail.com