Number of tweets collected per day during the whole collection period 22/12/2015 and 04/01/2016 at each filter level.

<p>Number of tweets collected per day during the whole collection period 22/12/2015 and 04/01/2016 at each filter level.</p

Flood map generated by twitter converted into FFC format for validation.

<p>White indicated no tweets. Colour bar units are relative floodiness. Top Left: Floodiness grid (64 × 64) over England and Wales on 28/10/2015 using (<i>r</i>, <i>α</i>) = (1.0, 0.15). Top Right: Showing only grid squares above threshold 0.1. Bottom Left: Counties with floods on 28/10/2015 according to Twitter. Bottom Right: Counties with floods on 28/10/2015 according to the FFC, with <i>g_h</i> set to 1 for flooded counties.</p

Precision, recall and parameter set obtained by maximising <i>F</i>_<i>β</i> scores using absolute and normalised floodiness.

<p>Precision, recall and parameter set obtained by maximising <i>F</i>_<i>β</i> scores using absolute and normalised floodiness.</p

Number of relevant tweets collected with location info in each field: GPS-tagged tweets, location field GPS coordinates, location field toponyms, message text toponyms.

<p>Number of relevant tweets collected with location info in each field: GPS-tagged tweets, location field GPS coordinates, location field toponyms, message text toponyms.</p

Total number of tweets with each kind of location information.

<p>Total number of tweets with each kind of location information.</p

Floodiness grid, 64 × 64, over the North East on 5/12/2015 between 4pm and 5pm using (<i>r</i>, <i>α</i>, <i>T</i>) = (1.0, 0.15, 0.1).

<p>White indicates no tweets or zero population. Colour bar indicates floodiness relative to daily max.</p

Number of tweets collected per day during the whole collection period 22/10/2015 and 25/11/2016.

<p>Number of tweets collected per day during the whole collection period 22/10/2015 and 25/11/2016.</p

Tuning absolute floodiness threshold <i>T</i> by varying text versus location weighting <i>r</i> and population scaling exponent <i>α</i>.

<p>Each point corresponds to the average precision and recall over 15 days for a different triple of <i>r</i>, <i>α</i>, <i>T</i>.</p

Tuning relative floodiness threshold <i>T</i> by varying text versus location weighting <i>r</i> and population scaling exponent α.

<p>Each point corresponds to the average precision and recall over 15 days for a different triple of <i>r</i>, <i>α</i>, <i>T</i>.</p

Total number of tweets remaining after each filter is applied and correlation of the number of tweets per day with FFC data.

<p>Total number of tweets remaining after each filter is applied and correlation of the number of tweets per day with FFC data.</p