Learn how Amenity Analytics’ NLP expertly handles the nuances and sophistication of human language. Amenity's unparalleled accuracy helps businesses make better decisions.
Thematic sentiment analysis is the process of identifying and categorizing feelings, opinions, and attitudes found within text documents. AI advancements has led to major improvements in the quality of sentiment data and the ways in which this data can be applied. Organizations are using thematic sentiment to evaluate and assess everything from SEC filings and earnings call transcripts to corporate documents and internal communications to social media, news articles, and online forums.
Sentiment analysis, also known as "opinion mining", gauges the predominant opinion toward a subject of interest (commonly referred to as an“entity”) such as people, places, organizations, locations, and things. Opinions may be classified as positive, negative, or neutral.
Thematic analysis provides a structured, systematic approach to understanding sentiment. Viewing sentiment data grouped by thematic events — for example,commentary on a product launch or a company’s growth forecast — makes it possible to spot patterns, trends, and outliers, and track these findings over time.
Organizations today find themselves having to access seemingly endless streams of text data: internal and external reports, online posts, transcripts,reviews, emails, blogs, news articles, and so forth.
While there are valuable nuggets of information waiting to be revealed within these data sources, the process of sifting, sorting and analyzing all of this information is no small feat. Such an endeavor requires a significant outlay of time and money, not to mention the knowledge of a domain expert to interpret the data correctly.
So how do organizations negotiate these obstacles? By using next-gen AI solutions that can extract usable insights from any text data source at scale,while also displaying a sophisticated understanding of human language.
We leverage Amenity’s latest ESG features, Materiality 2.0 and Greenwashing Analytics, to provide a debrief of Climate Week 2021. Find out who might be greenwashing and discover the positive narratives from the last 12 months. We also cover the noteworthy commitments, investments, or milestones of this year’s event.
As a lead-up to Climate Week, we expose who might be greenwashing, review the positive narratives from the last 12 months, and discuss what you should watch out for during this year’s event. This webinar recording is key for investors interested in diving into and monitoring the relationship between climate and corporate pronouncements in real-time.
This webinar explains why it’s crucial for analysts to include next-generation ESG data, as well as second-order information, as part of an effective investment strategy.
How do investors separate fact from fiction among net zero commitments made by the world's largest banks, when they invested $3.8 trillion in fossil fuels since the 2015 Paris Agreement? We apply our Greenwashing analytics on statements made by the banks vs external news coverage to determine which banks are keeping their net zero commitments, or falling behind.
Why packaged, static ESG data sets don’t cut it—how to win at ESG investing amidst a throng of competitors and an ocean of generic ESG data.
Evercore's latest COVID coverage noted that vaccine sentiment reached a several month low, so we explored further on this development using our COVID Dashboard to uncover two themes driving the drop. We also look at the combined sentiment of the three companies that are on the front lines of vaccine development: Pfizer, Moderna and AstraZeneca.
We take a look at the evolution of the ESG narrative from 3Q Earnings through the lens of Amenity Safeguard, our industry-leading natural language processing platform for ESG.
Sifting through management’s earnings commentary for key insights presents its own challenges as the lack of clarity from executives and the noise from all things Coronavirus makes it easy to overplay or underplay a decision. Expedia and Hilton Worldwide Holdings are two recent examples of how NLP (done right) can be a successful anticipatory tool with regards to a company’s fundamentals in a volatile market.
It’s no surprise that Zoom's revenue and cash generation growth has been stunning, but when we view the latest earnings through our NLP Insights Platform it returned surprising scores in terms of overall sentiment, margin and in particular, guidance which show a downward trend, so we explore further.
Here are 5 examples of how corporations and investors can use Amenity's NLP to systematically understand how ESG factors in the news drive company performance, with an unbiased dataset built around transparency and granularity.
ESG is one of many factors when it comes to assessing credit ratings. However, the increasing relevance of environmental and social issues warrants treating ESG as a core factor in credit analysis through the use of NLP.
In a follow-up to our previous Restaurant sector write-up we identify off-premise sales growth as an interesting variable to track. Takeout and delivery channels have been the primary focus for most restaurant companies as they attempt to minimize cash burn rates. BJ’s Restaurants (ticker: BJRI) is one interesting case study we explore in detail.
Executives from Intel and GenTrust join Amenity Analytics CEO Nate Storch to discuss the latest challenges and opportunities surrounding ESG.
We leveraged our NLP model to create the Amenity Coronavirus Tracker dashboard – a live feed which searches for relevant insights into the virus’ investment implications contained within news sources and earnings call transcripts. We highlight findings impacting retail, food delivery and teleconferencing.
Keep up to date with our analyses and how we're making changes.