Pythonism

code and the oracular

Archive for the ‘Text analysis’ Category

Simple Python Project: Markov Text

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consider this sentence

“the cat sat on the mat”

we can see the following about it

the word “the” is followed by “cat” and “mat”
the word “cat” is followed by “sat”
the word “sat” is followed by “on”
the word “on” is followed by “the”

so from this sentence we can construct a dictionary like this

catsat = {"the":["cat","mat"],
          "cat":["sat",],
          "sat":["on",],
          "on":["the",],
          "mat":[]}

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Written by Luke Dunn

December 31, 2015 at 9:09 am

New Concept – The Sentiment Ticker

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The Concept

The sentiment ticker is a small widget that sits on your computer’s desktop much like the conventional stock ticker. This widget connects to a central server cluster run by the provider. It provides a graphical/numerical display of various indices of market, political and consumer mood and feeling. The central servers poll blogs, tweets, journalistic articles and press releases constantly and perform sentiment analysis on this online content. Sentiment mining is looking for clusters of mood and emotion words in certain contexts. this has been shown to be useful, most notably recently when the Arab Spring was “predicted” (in hindsight) by analysing the sentiments of millions of bloggers, tweeters etc. a statistically significant spike was found in middle east mood just before the spring started.

Background

A stock ticker is a small program that stays open on your screen with real-time updated information on stock prices, and states of the various markets. It usually shows a graph or two and required price information you have set it for. All traders use them perennially.

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Written by Luke Dunn

December 6, 2011 at 1:53 pm