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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/04/warren-buffet-sentiment.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p>Warren Buffett — known as the &quot;Oracle of Omaha&quot; —<strong> </strong>is<strong> </strong>one of the most successful investors of all time. Wherever the winds of the market may blow, he always seems to find a way to deliver impressive returns for his investors and his company, Berkshire Hathaway. Every year he authors his famous &quot;<a target="_blank" rel="nofollow" href="http://www.berkshirehathaway.com/letters/letters.html">shareholder letter</a>&quot; with his musing about the market and investment strategy and — perhaps as reflects his continued success — this <a target="_blank" rel="nofollow" href="http://michaeltoth.me/sentiment-analysis-of-warren-buffetts-letters-to-shareholders.html">sentiment analysis of his letters by data scientist Michael Toth</a> shows that the tone has been generally positive over time. Only five of the forty years of letters show an average negative sentiment: those correspond to market downturns in 1987, 1990, 2001/2002 and 2008.</p>
<p><a target="_blank" rel="nofollow" href="http://michaeltoth.me/sentiment-analysis-of-warren-buffetts-letters-to-shareholders.html"><img title="Berkshire_hathaway_sentiment" alt="Berkshire_hathaway_sentiment" src="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01b8d279412f970c-800wi" border="0"></a></p>
<p>Michael used the <a target="_blank" rel="nofollow" href="https://mran.microsoft.com/documents/what-is-r/">R language</a> to generate a sentiment score for each letter, and the process was surprisingly simple (you can <a target="_blank" rel="nofollow" href="https://github.com/michaeltoth/michaeltoth/blob/master/content/berkshire_hathaway_sentiment.Rmd">find the R code here</a>). The letters are published as PDF documents, from which the text can be extracted using the <code>pdf_text</code> function in the <a target="_blank" rel="nofollow" href="https://mran.microsoft.com/package/pdftools/">pdftools package</a>. Then you can use the <a target="_blank" rel="nofollow" href="https://mran.microsoft.com/package/tidytext/">tidytext package</a> to decompose the letters into individual words, whose Bing sentiment score can be calculated using its <code><a target="_blank" rel="nofollow" href="https://www.rdocumentation.org/packages/tidytext/versions/0.1.2/topics/get_sentiments">get_sentiments</a></code> function. From there, a simple <a target="_blank" rel="nofollow" href="http://ggplot2.tidyverse.org/reference/geom_bar.html">ggplot2 bar chart</a> is used to show the average sentiment scores for each letter.</p>
<p>For more on the sentiment of Warren Buffett's shareholder letters, including an analysis of the most-used positive and negative words, follow the link to the complete blog post below.</p>
<p>Michael Toth: <a target="_blank" rel="nofollow" href="http://michaeltoth.me/sentiment-analysis-of-warren-buffetts-letters-to-shareholders.html">Sentiment Analysis of Warren Buffett's Letters to Shareholders</a></p>
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