Social media data

As explained in Investing for Programmers

Social media data is information collected from user-generated content and interactions on social media platforms.

Social media data is a form of nonfinancial data collected from user-generated content and interactions. Real-time posts can become inputs to trading algorithms because public statements may influence share prices. section 11.1

Use it with attention to relevance and limitations:

• Treat social media signals as more relevant to consumer-oriented companies than to business-to-business companies. section 11.1
• Compare social media evidence with financial data rather than assuming it replaces balance-sheet information. section 11.1

Figure 11.1 Three types of data flow can lead to insights, and nonfinancial data, being the newest of them, is especially interesting.

Use the data-flow figure to place social media data within the broader movement toward nonfinancial inputs and market insight. section 11.1

How Investing for Programmers covers it

How deep it goes

Defines the category, market role, and sector relevance but stops short of collection, processing, or implementation details.

Examples

Uses real-time social media posts and politically driven market reactions as examples of potentially influential signals.

What it assumes

Assumes familiarity with investors, share prices, and trading algorithms while distinguishing financial from nonfinancial data.

What you can do after

Evaluate social media data as a sector-sensitive trading input rather than a universal substitute for financial information.

How it connects

Connects nonfinancial data with financial data, trading algorithms, share prices, consumer companies, and B2B companies.

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Related concepts

• nonfinancial datakind of · Nonfinancial data is quantifiable information about an entity or its environment that is not part of its financial accounts.
• stock share pricemeasures · A stock share price is the market value of one share of a publicly traded company or security at a particular time.
• retrieval-augmented generationused by · Retrieval-augmented generation is a technique that retrieves relevant information from external sources and supplies it as context to a generative model when producing an output.

This explainer was generated by Manning's knowledge graph from the text of Investing for Programmers. The section links point to the parts of the book it draws on.