Table summarizing the content of our extracted topics.

<p>The classification was created by manual reading of the underlying news records that included the topic, at least to some extent. The right column shows the number of stocks that contained that topic out of the 206 analyzed stocks. See text for more information.</p

List of the 9 selected topics for “Toyota”.

<p>Their estimated “fraction of volume explained” (FVE) are shown as well. Topic distributions are summarized with their top most frequent 3–5 words. For a full description of the topic distributions, see the supporting information.</p

Flowchart summarizing the procedure followed in our analyses.

<p>The number in parentheses indexes the step. Step (1) selects the news records associated with a given term, here the name of a company, such as Toyota. Step (2-a) applies the Latent Dirichlet Allocation (LDA) that decomposes any document as a mixture of different topics. Step (3-a) implements a constrained LASSO regression. The percentage shown in step (3-b) denotes the estimated impact of each topic. The percentage shown in step (4) is the “fraction of (trading volume) peaks explained” (FPE) by news, which is our metric to assess the quality of our methodology (see text).</p

Pictorial illustration of “peak days” of normalized trading volume.

<p>The black line shows the de-trended trading volume of Toyota stock for the period from January 2003 to June 2011. The red dots indicate the “peak days” selected by the method described in the text. There are 119 “peak days” for the entire period from January 2003 to June 2011.</p

Selected topic learned by LDA for Toyota.

<p>Selected topics learned by LDA and the associated news volume estimated using <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064846#pone.0064846.e005" target="_blank">equation (1</a>) for the term “Toyota.” The top three words for these topics were: (A) Toyota, recall, safety; (B) financial, crisis, economy; (C) Japan, production, earthquake; (D) team, F1, race.</p

Network extracted for Microsoft and Yahoo.

<p>Nodes are topics and links between two topics quantify the degree of similarity associated with their word distributions.</p

Comparison between estimated and actual trading volume.

<p>Estimated (red dashed line) and actual (black continuous line) trading volume for the four companies: (A) Toyota, (B) Yahoo, (C) Best Buy, and (D) BP. The number <i>K</i> of sufficient selected topics is 9 for Toyota, 4 for Yahoo, 3 for Best Buy, and 5 for BP.</p

Network of topics extracted for the 206 US companies.

<p>The links between two topics quantifying the degree of similarity associated with their word distributions, as explained in the text. The six red arrows depict the zones that are magnified in Fig. 10.</p

Comparison between the time evolution of trading volume and aggregate news volume for Toyota.

<p>Black continuous line plots trading volume and red dashed line plots aggregate news volume. The inset plots the trading volume as a function of the concomitant news volume.</p