News Monitoring for Banking & Finance
Overview The metaverse has been around for more than 30 years, yet news monitoring shows that media frenzy has piqued lately due to some major factors in recent times. After all, when a tech mammoth like Microsoft invests US$69 Bn in purchasing Activision Blizzard, owner of legendary video game franchises like Call of Duty and Candy Crush Saga, in order to have a foothold in the metaverse, it gets noticed. Media hype also gained momentum after Facebook changed its name to Meta in a major rebrand after announcing its investment decision, notwithstanding the hilarious memes that mushroomed after the news.
Metaverse news analysis shows that investors are confident that the metaverse will ultimately replace live entertainment, something along the lines of Lil Nas X’s virtual performance in Robolox. Unlike virtual reality (VR) and augmented reality (AR) games today, where one picks up where one has stopped, in an idealistic metaverse, the experience is in perpetuity, where everything continues despite a person logging off. Tech investors and companies, NFT shareholders, investors in AI and emerging technologies, stock investors, the cryptocurrency market, and others are betting on a whole new economy, estimated to be worth trillions of dollars, that can be built in this virtual world, per news sentiment analysis. Given this background, we decided to analyze sentiment surrounding the metaverse. We analyzed over 10,000 news articles talking about Metaverse using Repustate’s news monitoring tool to know exactly what the dominant topics in all this big data were, and what they were all about.
What Insights Did We Find When We Scanned News Sites For Metaverse? Below these and other major insights, and the factors behind them, in detail. 1. Sentiment trend 2. Sentiment distribution trend and Overall sentiment 3. Size of Data Source 4. Most common Entities 5. Average sentiment score 6. Language-based sentiment analysis 7. Sentiment score of specific terms
How News Monitoring Works Machine learning-based news monitoring is a culmination of several algorithms working in sync. There are 4 steps to the entire process, comprising several ML subtasks that include video content analysis, text analytics, natural language processing, sentiment analysis, and others. In a brief overview of the process Step 1 comprises data collection i.e. all the news sources for your subject Step 2 includes processing of all this data to extract entities, aspects, video analysis, and the like Step 3 is where the processed data gets analyzed by a sentiment analysis API; And Step 4 is eventually when all the news monitoring insights are presented on a visualization dashboard in the form of charts and graphs.
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