PUMP: The World's First and Only Comprehensive Social Media Analytics Platform for Commodity Traders

Social media has grown to be a powerful determinant of prices and trading sentiment in a variety of financial markets, including commodity markets. PUMP is the world’s first comprehensive, NLP-based social media analytics platform designed with commodity traders and investors in mind. There is a reason why this niche is deserted – measuring social sentiment for commodity assets is challenging. Read on to see why.

Tracking Social Sentiment for Commodity Assets

PUMP revolutionises the way commodity traders approach social media analytics by providing the first and only tool designed specifically for tracking social sentiment related to commodity assets. Leveraging advanced AI algorithms, including LLM (Large Language Models), PUMP optimises the identification and analysis of social sentiment specifically for commodity assets.
There is an abundance of tools that measure social sentiment for brands and consumer products. However, measuring sentiment for commodity assets is a specialised task that requires unique approaches.

Addressing Challenges in Commodity Social Listening

Finance-Specific NLP Models for Accurate Asset Identification
Commodity social listening presents unique challenges that traditional social media analytics platforms often fail to address. For instance, commodities like milk, coffee, orange juice, and even gold are frequently mentioned on social media, but not always in the context of commodity trading or finance. People might discuss their coffee cravings, gold credit cards, or favorite orange juice brand, making it essential to filter out irrelevant signals.
PUMP’s advanced pre-trained NLP models are designed to identify domain-specific conversations related to commodities.
PUMP utilises finance-specific NLP models to accurately identify the correct mentions of commodity assets. By distinguishing between discussions about coffee as a beverage and coffee futures or price movements, PUMP ensures that traders receive relevant social signals pertaining to commodity trading.
Specialised and Nuanced Discussions
Commodity traders form a distinct segment with their own specific needs and preferences. Unlike many crypto or stock traders, most commodity traders tend to be highly specialised and deeply involved in their field. Consequently, their social media discussions are more nuanced and rarely generate the same level of massive engagement that is characteristic of crypto or stock discussions.
Recognising the value of such low-engagement discussions, PUMP excels at sourcing specialised and obscure conversations about commodities. This allows us to capture valuable insights that may not surface in broader social media conversations.
The Forward-Looking Nature of Commodity Trading Discussions
Commodity traders predominantly use futures contracts for their trading activities, which are inherently forward-looking. These futures contracts are often settled two months or more in the future. Given the nature of these financial instruments, commodity traders and analysts often use future-oriented vocabulary in social media conversations. For example, conversations might revolve around longer-term predictions such as "Oil will possibly decline by autumn" or "I think the soybean market will stabilise by year-end."
Identifying the timeframe of these forward-looking discussions is vital for effective social listening in commodity trading. PUMP excels in this aspect by continuously fine-tuning its pre-trained models to accurately identify the timeframe being referred to.

Commodity asset discussions on social media are challenging to measure due to their lower signal volumes, massive amounts of mentions not relevant to commodity traders’ needs, and very nuanced future-oriented predictions and opinions. Under the hood, PUMP operates a sophisticated system that delves beneath the surface to identify only the signals relevant to commodity trading and investing. We provide commodity traders with the most accurately calibrated and high-quality social sentiment data available, an undertaking few others dare to tackle.