- The Future of Fake News - Oct 13, 2020.
Let's talk about misleading communications in the digital era.
- DIY Election Fraud Analysis Using Benford’s Law - Sep 15, 2020.
In this article, we will talk about a Do-It-Yourself approach towards election analysis and coming to a conclusion whether the elections were conducted fairly or not.
- Predicting the President: Two Ways Election Forecasts Are Misunderstood - Mar 27, 2020.
With election cycles always seeming to be in season, predictions on outcomes remain intriguing content for the voting citizens. Misinterpretation of election forecasts also runs rampant, and can impact perceptions of candidates and those who post these predictions. A better fundamental understanding of probability can help improve our collective notion of futurism, and how we monitor elections.
- Prepare for a Long Battle against Deepfakes - Feb 21, 2020.
While deepfakes threaten to destroy our perception of reality, the tech giants are throwing down the gauntlet and working to enhance the state of the art in combating doctored videos and images.
- The Mueller Report Word Cloud: A brief tutorial in R - Apr 22, 2019.
Word clouds are simple visual summaries of the mostly frequently used words in a text, presenting essentially the same information as a histogram but are somewhat less precise and vastly more eye-catching. Get a quick sense of the themes in the recently released Mueller Report and its 448 pages of legal content.
- The brain as a neural network: this is why we can’t get along - Dec 19, 2018.
This article sets out to answer the question: what insights can we gain about ourselves by thinking of the brain as a machine learning model?
- Analytically Speaking Featuring Pedro Saraiva, July 12 - Jul 7, 2017.
Former academician and now Portugal MP Pedro Saraiva says that Parliaments and societies will improve if more people with a good statistical background become MP. Learn about the paradoxes and issues in statistics and politics.
- Why Data Science Argues against a Muslim Ban - Jun 24, 2017.
From the perspective of data science, a Muslim ban would weaken security, not strengthen it.
- Machine Learning Finds “Fake News” with 88% Accuracy - Apr 12, 2017.
In this post, the author assembles a dataset of fake and real news and employs a Naive Bayes classifier in order to create a model to classify an article as fake or real based on its words and phrases.
- What Happened Last Night in Sweden: Data Science vs Fake News - Mar 22, 2017.
During a rally in February, President Trump had these disparaging words about Sweden’s humane immigration policy... but nothing of note actually happened the previous night in Sweden.
- Interview: UN/WDC “Data For Climate Action” Challenge – What Data Scientists Need to Know - Mar 13, 2017.
We ask UN Global Pulse Director about the 'Data For Climate Action' Challenge, the best sources of climate data, examples of using data for climate mitigation and climate adaptation, and resources for convincing climate change skeptics.
- Data Science vs Fake News Contest - Feb 27, 2017.
Submit a story that clearly exposes a false claim in the news, using data and visualization. This contest is sponsored by KDnuggets, Data For Democracy, and data.world. Submissions due March 10, 2017.
- Data Scientists Strongly Oppose Trump Immigration Ban - Feb 21, 2017.
Latest poll of nearly 1000 analytics professionals and data scientists who read KDnuggets shows that 75% worldwide and 77% in the US oppose Trump Immigration Ban. The poll results reveal sharp polarization, with strong views prevailing on both sides.
- Data for Democracy: The First Two Months of D4D - Feb 20, 2017.
Let’s hear about how Data Science is used for democracy and well being of human societies by Data for Democracy organisation.
- New Poll: Do you support Trump Immigration Ban? - Feb 9, 2017.
Express your opinion about Trump Immigration ban and find out what does Google Autocomplete offers when you search for "Trump Immigration".
- Cartoon: Make Data Great Again - Aug 13, 2016.
This KDnuggets cartoon considers a speech that a certain presidential candidate can give on a topic of Big Data.
- Political Data Science: Analyzing Trump, Clinton, and Sanders Tweets and Sentiment - Jun 18, 2016.
This post shares some results of political text analytics performed on Twitter data. How negative are the US Presidential candidate tweets? How does the media mention the candidates in tweets? Read on to find out!
- Global Strategy Group: Senior Associate, Analytics - Jun 17, 2016.
Seeking a Senior Associate to work with our team to help develop new products and methodologies, and integrate analytics capabilities into GSG’s research services.
- Trump vs Clinton – What are the Odds? - Mar 7, 2016.
Even with 5% advantage for Clinton, statistical analysis and examining how undecided break towards these candidates, we estimate a 25%-30% chance that Trump would be elected president.
- Visualizing Unstructured Analysis – Elections, Words, and Zika virus - Feb 15, 2016.
Unstructured data has proven to be a big analytics challenge. This week in the Data Driven Digest, we’re serving up some ingenious visualizations of unstructured data and making it talk.
- Money vs Votes in New Hampshire Primary – SuperPACs not very effective - Feb 12, 2016.
We examine the money and votes in New Hampshire 2016 Primary. Over $100 million was spent by all campaigns, with hugely varying results, and no apparent correlation between money and votes.
- Money does buy votes, unless you are Jeb Bush - Feb 3, 2016.
Can money buy votes? In Iowa republican caucuses Jeb Bush spent about $2,700/per vote, with little to show. However, without Jeb, there is a strong correlation between money and votes, with $210/vote on average. We also find that spending more time in Iowa does not help.
- Four Major Predictions for Predictive Analytics and Big Data in 2016 - Feb 2, 2016.
2016 will usher in some unmissable results of the Information Age’s latest contribution, the more effective execution of major operations across sectors with predictive analytics.