Twitter NLP, M&A, and Power

#24 - Social Media Deconstructed

August 14, 2024

Social media is the driving force behind our hyper-connected world, wielding unparalleled power to shape opinions, drive consumer behavior, and fuel cultural revolutions. We attempt to transform the way you think of this digital powerhouse’s role in our lives through our unique financial, tech, and sustainability centric analyses.

📱 New Social Media Business Models

An Innovative approach to change social media business models

Social media platforms are facing growing pressure to evolve their traditional, ad-driven business models. As these platforms confront ethical concerns and public scrutiny, new approaches are being explored to create a more balanced and sustainable online environment.

Current State: Platforms like Facebook and Twitter use algorithms that maximize user engagement, often at the cost of promoting divisive content.

Alternative Algorithms: Public scrutiny and government backlash, among other factors have forced industries to consider different models.

What is Required: A model that focuses more on promoting quality content, rather than purely user engagement.

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What we ask of You: Email us at [email protected] or reply to this email with ideas for newer models. You can be as technical as you want. The best response may receive a special reward from our team!

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Below are some ideas to guide your answer

Technical Considerations:

  • Critiques of the Attention Economy: The focus on capturing user attention has been criticized for encouraging misinformation and emotional manipulation. Moving towards models that value content quality is becoming essential.

  • Decentralized Models: Interest is growing in decentralized platforms that reduce data exploitation and offer greater user autonomy.

—💥NEWSFLASH💥—

🧾RECENT STORIES

FINANCE

M&A Strategy & Modeling for Social Media Firms

Mergers and acquisitions (M&A) in the social media industry require a distinct financial approach. For example, Facebook's $1 billion acquisition of Instagram in 2012 focused on Price-to-Sales (P/S) ratios and user growth rather than traditional Price-to-Earnings (P/E) ratios.

Social media firms typically have higher P/S ratios reflecting their potential to growth through network effects, and lower P/E ratios due to them being in an early stage of profitability.

💡P/E Ratio: The Price-to-Earnings (P/E) ratio measures a company's current share price relative to its EPS, indicating how much investors are willing to pay for each dollar of earnings

Microsoft’s $26.2 billion acquisition of LinkedIn in 2016 is another great example.

Microsoft’s valuation included a higher-than-average P/S ratio of 7.7x, due to LinkedIn’s monetization potential. The DCF model emphasized future cash flows from premium services, reflecting the stronger industry’s focus on growth rather than current earnings.

Scenario analysis is particularly important. Facebook’s $19 billion acquisition of WhatsApp in 2014 involved extensive analysis of data privacy regulations and integration, highlighting the importance of testing numerous assumptions in valuation models for social media firms in the digital age.

Life Cycle (Most Social Media Firms are in the Growth Stage)

TECHNOLOGY

How Natural Language Processing is Being Utilized by Social Media Apps

Natural Language Processing (NLP) is a branch of artificial intelligence (AI) focused on enabling machines to understand, interpret, and generate human language.

It involves several key processes, including:

  • tokenization (breaking down text into smaller units),

  • part-of-speech tagging (identifying grammatical categories),

  • entity recognition (detecting names of people, places, etc.),

  • sentiment analysis (determining the emotion or opinion behind the text).

💡Tokenization: It is like breaking down a big paragraph into smaller, manageable pieces. Imagine you have a long sentence, and you want to understand each word separately.

It splits a sentence into individual words or "tokens."

Sentiment Analysis

Machine learning algorithms and deep learning models are used to train systems on vast amounts of data, enabling them to recognize patterns and make predictions based on linguistic input.

Twitter uses NLP to gauge public sentiment by analyzing tweets. This helps in understanding public opinion on various topics, monitoring brand reputation, and identifying trends.

SUSTAINABILITY

Power Hungry Neural Networks That Target You

As neural networks power the algorithms behind social media, their energy consumption has become a growing concern. These AI models, responsible for personalized recommendations and content curation, require vast computational resources, leading to an immense demand for energy.

Carbon Footprint From Training a Large NLP Network

Image Source: ekamperi.github.io

Recent studies highlight the environmental impact of these neural networks, revealing that their energy appetite is nearly insatiable. This issue is compounded by the continuous training and fine-tuning of models A neural network can achieve 80% accuracy in a day but only reach 85% after a month.

💡Neural Network: A neural network is a computational model inspired by the structure of the human brain, consisting of layers of nodes. These networks process and analyze complex data allowing them to learn patterns and make decisions based on input data.

To address this challenge, there is a push for more efficient AI technologies and sustainable practices within the industry. Reducing the energy consumption of neural networks through innovation is crucial for mitigating their environmental impact.

💡STAT OF THE WEEK💡

Reach out to [email protected] or reply to this email for inquiries.

Editor: Rahul

Authors: Hardit, Amy, Kabeer, Yash, Hoshner, Rahul