search engine data
ALERTA-Net: A Temporal Distance-Aware Recurrent Networks for Stock Movement and Volatility Prediction
Wang, Shengkun, Bai, YangXiao, Fu, Kaiqun, Wang, Linhan, Lu, Chang-Tien, Ji, Taoran
For both investors and policymakers, forecasting the stock market is essential as it serves as an indicator of economic well-being. To this end, we harness the power of social media data, a rich source of public sentiment, to enhance the accuracy of stock market predictions. Diverging from conventional methods, we pioneer an approach that integrates sentiment analysis, macroeconomic indicators, search engine data, and historical prices within a multi-attention deep learning model, masterfully decoding the complex patterns inherent in the data. We showcase the state-of-the-art performance of our proposed model using a dataset, specifically curated by us, for predicting stock market movements and volatility.
China and scientists dismiss study suggesting coronavirus spread in August 2019
LONDON โ Beijing dismissed as "ridiculous" a Harvard Medical School study of hospital traffic and search engine data that suggested the novel coronavirus may already have been spreading in China last August, and scientists said it offered no convincing evidence of when the outbreak began. The research, which has not been peer-reviewed by other scientists, used satellite imagery of hospital parking lots in Wuhan -- where the disease was first identified in late 2019 -- and data for symptom-related queries on search engines for terms such as "cough" and "diarrhea." The study's authors said increased hospital traffic and symptom search data in Wuhan preceded the documented start of the coronavirus pandemic, in December 2019. "While we cannot confirm if the increased volume was directly related to the new virus, our evidence supports other recent work showing that emergence happened before identification at the Huanan Seafood market (in Wuhan)," they said. Paul Digard, an expert in virology at the University of Edinburgh, said that using search engine data and satellite imagery of hospital traffic to detect disease outbreaks "is an interesting idea with some validity."
China pushes back against Harvard coronavirus study
Beijing has dismissed as "ridiculous" a Harvard Medical School study of hospital traffic and search engine data that suggested the new coronavirus may already have been spreading in China last August, and scientists said it offered no convincing evidence of when the outbreak began. Chinese Foreign Ministry spokeswoman Hua Chunying, asked about the research at a news briefing on Tuesday, said: "I think it is ridiculous, incredibly ridiculous, to come up with this conclusion based on superficial observations such as traffic volume." The research, which has not been peer-reviewed by other scientists, used satellite imagery of hospital parking lots in Wuhan - where the disease was first identified in late 2019 - and data for symptom-related queries on search engines for things such as "cough" and "diarrhoea". The study's authors said increased hospital traffic and symptom search data in Wuhan preceded the documented start of the coronavirus pandemic in December 2019. "While we cannot confirm if the increased volume was directly related to the new virus, our evidence supports other recent work showing that emergence happened before identification at the Huanan Seafood market (in Wuhan)," they said.
Spikes in search engine data predict when drugs will be recalled
Could internet searches identify dodgy drugs? A Microsoft researcher has trained an algorithm to predict whether a drug will be recalled, using queries made through Microsoft's Bing search engine. "We know that every once in a while there will be a batch of a pharmaceutical drug that will have something wrong about it," says Elad Yom-Tov at Microsoft Research in Israel. "People will start asking about that drug more often or more than they usually do." Pharmaceutical companies and regulators such as the US Food and Drug Administration (FDA) monitor drugs on the market to keep tabs on adverse effects and potential faulty batches.
What are data scientists interested in? Insights from our search engine data
We've gathered data from our newly created DSC search box, and based on 20,000 search queries over the last four months (most of them in the last 30 days), we discovered that the top queries so far are: The number in parenthesis indicates the number of queries, over the last four months. Note that some keywords have a high number of queries, because they are listed as top queries in one of our popular articles. Starred queries were not promoted in any way. Today we created a new data science search engine, ad-free, where anyone can submit his blog for indexation. We invite you to try it and share it.