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timtamimi/index.js

Created January 28, 2020 13:55
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Sentiment analysis script
Raw
index.js
let fs = require("fs");
const csv = require("csv-parser");
var Sentiment = require("sentiment");
var sentiment = new Sentiment();
require("dotenv").config();
const { CanvasRenderService } = require("chartjs-node-canvas");
const percentile = require("stats-percentile");
let output = [];
fs.createReadStream("comments.csv")
.pipe(csv())
.on("data", row => {
//First, for each row, we discount the first two words as those are the poster's name.
//I did not cleanse names out because names appear in the body of a comment (mentions) anyway, but I can reduce ambiguity by trimming out the first couple of words so that the sentiment analysis is focused on the body of the text.
var comment = row.Comment
? row.Comment.substr(row.Comment.indexOf(" ") + 1).substr(
row.Comment.substr(row.Comment.indexOf(" ") + 1).indexOf(" ") + 1
)
: null;
if (comment) {
var result = sentiment.analyze(comment); //run the comment through sentiment analysis
output.push({ comment: comment, result: result }); //add output to array
} else {
var result = sentiment.analyze(row["0"]); //run the comment through sentiment analysis
output.push({ comment: row["0"], result: result }); //add output to array
}
})
.on("end", () => {
console.log("CSV file successfully processed");
//defining percentiles
let p75 = percentile(
output.map(row => row.result.comparative),
75
);
let p50 = percentile(
output.map(row => row.result.comparative),
50
);
let p25 = percentile(
output.map(row => row.result.comparative),
25
);
//assigning each data point to a percentile
output.map(dataPoint => {
dataPoint["quartile"] =
dataPoint.result.comparative >= p75
? 4
: dataPoint.result.comparative >= p50
? 3
: dataPoint.result.comparative >= p25
? 2
: 1;
return dataPoint;
});
console.log("Drawing the results");
(async () => {
const width = 400; //px
const height = 400; //px
const configuration = {
type: "bar",
options: { legend: { display: false } },
data: {
labels: [
"Very positive (Q4)",
"Positive (Q3)",
"Negative (Q2)",
"Very negative (Q1)"
],
datasets: [
{
data: [
output.filter(row => row.quartile == 4).length,
output.filter(row => row.quartile == 3).length,
output.filter(row => row.quartile == 2).length,
output.filter(row => row.quartile == 1).length
],
backgroundColor: [
"rgba(255, 99, 132, 0.2)",
"rgba(54, 162, 235, 0.2)",
"rgba(255, 206, 86, 0.2)",
"rgba(75, 192, 192, 0.2)",
"rgba(153, 102, 255, 0.2)",
"rgba(255, 159, 64, 0.2)"
],
borderColor: [
"rgba(255,99,132,1)",
"rgba(54, 162, 235, 1)",
"rgba(255, 206, 86, 1)",
"rgba(75, 192, 192, 1)",
"rgba(153, 102, 255, 1)",
"rgba(255, 159, 64, 1)"
],
borderWidth: 1
}
]
}
};
const canvasRenderService = new CanvasRenderService(
width,
height,
ChartJS => {}
);
const dataUrl = await canvasRenderService.renderToDataURL(configuration);
let tableRows = output.map(function(row, index) {
return `<tr>
<td>${index}</td>
<td>redacted</td>
<td>${row.result.score}</td>
<td>${row.result.comparative}</td>
<td>${row.quartile}</td>
<td>
${
row.quartile == 4
? "Very positive"
: row.quartile == 3
? "Positive"
: row.quartile == 2
? "Negative"
: "Very negative"
}
</td>
</tr>`;
});
fs.writeFile(
"./output.html",
`
<html>
<head>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/bootstrap-table/1.15.5/bootstrap-table.min.css" integrity="sha256-ok93TPAnFIabkUGZJ1a3U+xTyGK1IIP1/FpauAIKEo4=" crossorigin="anonymous" />
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/4.4.1/css/bootstrap.css" integrity="sha256-A47OwxL/nAN0ydiDFTSGX7ftbfTJTKgiJ0zqCuTPDh4=" crossorigin="anonymous" />
<script src="https://cdnjs.cloudflare.com/ajax/libs/bootstrap-table/1.15.5/bootstrap-table.min.js" integrity="sha256-i6G9CgAfmcq/7vYTD52U9501fb2XJiFGPMRGKn0QV7E=" crossorigin="anonymous"></script>
</head>
<img src="${dataUrl}"/>
<table class="table">
<thead>
<tr>
<th>Row number</th>
<th>Comment text</th>
<th>Score</th>
<th>Comparative score</th>
<th>Quartile</th>
<th>Sentiment derived from quartile</th>
</tr>
</thead>
<tbody>
${tableRows}
</tbody>
</table>
</html>
`,
function(err) {
if (err) {
return console.log(err);
}
console.log("The file was saved!");
}
);
})();
});
Raw
sample-output.html
<html>
<head>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/bootstrap-table/1.15.5/bootstrap-table.min.css" integrity="sha256-ok93TPAnFIabkUGZJ1a3U+xTyGK1IIP1/FpauAIKEo4=" crossorigin="anonymous" />
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/4.4.1/css/bootstrap.css" integrity="sha256-A47OwxL/nAN0ydiDFTSGX7ftbfTJTKgiJ0zqCuTPDh4=" crossorigin="anonymous" />
<script src="https://cdnjs.cloudflare.com/ajax/libs/bootstrap-table/1.15.5/bootstrap-table.min.js" integrity="sha256-i6G9CgAfmcq/7vYTD52U9501fb2XJiFGPMRGKn0QV7E=" crossorigin="anonymous"></script>
</head>
<img src="data:image/png;base64,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"/>
<table class="table">
<thead>
<tr>
<th>Row number</th>
<th>Comment text</th>
<th>Score</th>
<th>Comparative score</th>
<th>Quartile</th>
<th>Sentiment derived from quartile</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>1</td>
<td>redacted</td>
<td>3</td>
<td>1</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>2</td>
<td>redacted</td>
<td>6</td>
<td>0.16216216216216217</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>3</td>
<td>redacted</td>
<td>3</td>
<td>1.5</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>4</td>
<td>redacted</td>
<td>4</td>
<td>0.21052631578947367</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>5</td>
<td>redacted</td>
<td>2</td>
<td>0.14285714285714285</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>6</td>
<td>redacted</td>
<td>4</td>
<td>2</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>7</td>
<td>redacted</td>
<td>4</td>
<td>1.3333333333333333</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>8</td>
<td>redacted</td>
<td>4</td>
<td>0.6666666666666666</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>9</td>
<td>redacted</td>
<td>5</td>
<td>0.11363636363636363</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>10</td>
<td>redacted</td>
<td>3</td>
<td>0.3333333333333333</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>11</td>
<td>redacted</td>
<td>5</td>
<td>0.8333333333333334</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>12</td>
<td>redacted</td>
<td>-2</td>
<td>-0.5</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>13</td>
<td>redacted</td>
<td>4</td>
<td>0.8</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>14</td>
<td>redacted</td>
<td>5</td>
<td>0.7142857142857143</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>15</td>
<td>redacted</td>
<td>-3</td>
<td>-0.10344827586206896</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>16</td>
<td>redacted</td>
<td>-3</td>
<td>-0.12</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>17</td>
<td>redacted</td>
<td>-1</td>
<td>-0.015625</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>18</td>
<td>redacted</td>
<td>1</td>
<td>0.1111111111111111</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>19</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>20</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>21</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>22</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>23</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>24</td>
<td>redacted</td>
<td>3</td>
<td>0.13043478260869565</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>25</td>
<td>redacted</td>
<td>7</td>
<td>0.4117647058823529</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>26</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>27</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>28</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>29</td>
<td>redacted</td>
<td>1</td>
<td>0.058823529411764705</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>30</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>31</td>
<td>redacted</td>
<td>5</td>
<td>0.08064516129032258</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>32</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>33</td>
<td>redacted</td>
<td>5</td>
<td>0.5</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>34</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>35</td>
<td>redacted</td>
<td>1</td>
<td>0.125</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>36</td>
<td>redacted</td>
<td>7</td>
<td>0.3684210526315789</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>37</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>38</td>
<td>redacted</td>
<td>-3</td>
<td>-0.42857142857142855</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>39</td>
<td>redacted</td>
<td>3</td>
<td>0.15</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>40</td>
<td>redacted</td>
<td>3</td>
<td>0.3</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>41</td>
<td>redacted</td>
<td>6</td>
<td>0.14634146341463414</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>42</td>
<td>redacted</td>
<td>1</td>
<td>0.08333333333333333</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>43</td>
<td>redacted</td>
<td>1</td>
<td>0.05555555555555555</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>44</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>45</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>46</td>
<td>redacted</td>
<td>1</td>
<td>0.09090909090909091</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>47</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>48</td>
<td>redacted</td>
<td>3</td>
<td>0.375</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>49</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>50</td>
<td>redacted</td>
<td>5</td>
<td>0.5555555555555556</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>51</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>52</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>53</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>54</td>
<td>redacted</td>
<td>6</td>
<td>0.3333333333333333</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>55</td>
<td>redacted</td>
<td>1</td>
<td>0.02857142857142857</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>56</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>57</td>
<td>redacted</td>
<td>2</td>
<td>0.25</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>58</td>
<td>redacted</td>
<td>1</td>
<td>0.16666666666666666</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>59</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>60</td>
<td>redacted</td>
<td>3</td>
<td>0.21428571428571427</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>61</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>62</td>
<td>redacted</td>
<td>-1</td>
<td>-0.1</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>63</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>64</td>
<td>redacted</td>
<td>5</td>
<td>0.23809523809523808</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>65</td>
<td>redacted</td>
<td>8</td>
<td>0.15384615384615385</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>66</td>
<td>redacted</td>
<td>3</td>
<td>0.25</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>67</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>68</td>
<td>redacted</td>
<td>3</td>
<td>0.10714285714285714</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>69</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>70</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>71</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>72</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>73</td>
<td>redacted</td>
<td>5</td>
<td>0.1724137931034483</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>74</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>75</td>
<td>redacted</td>
<td>3</td>
<td>0.11538461538461539</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>76</td>
<td>redacted</td>
<td>5</td>
<td>0.2777777777777778</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>77</td>
<td>redacted</td>
<td>1</td>
<td>0.017857142857142856</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>78</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>79</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>80</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>81</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>82</td>
<td>redacted</td>
<td>1</td>
<td>0.03333333333333333</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>83</td>
<td>redacted</td>
<td>2</td>
<td>0.2857142857142857</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>84</td>
<td>redacted</td>
<td>3</td>
<td>0.6</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>85</td>
<td>redacted</td>
<td>9</td>
<td>0.5</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>86</td>
<td>redacted</td>
<td>4</td>
<td>0.14285714285714285</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>87</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>88</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>89</td>
<td>redacted</td>
<td>2</td>
<td>0.10526315789473684</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>90</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>91</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>92</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>93</td>
<td>redacted</td>
<td>7</td>
<td>0.11475409836065574</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>94</td>
<td>redacted</td>
<td>1</td>
<td>0.03225806451612903</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>95</td>
<td>redacted</td>
<td>3</td>
<td>0.21428571428571427</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>96</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>97</td>
<td>redacted</td>
<td>6</td>
<td>0.1935483870967742</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>98</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>99</td>
<td>redacted</td>
<td>3</td>
<td>0.15</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>100</td>
<td>redacted</td>
<td>5</td>
<td>0.15625</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>101</td>
<td>redacted</td>
<td>3</td>
<td>0.42857142857142855</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>102</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>103</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>104</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>105</td>
<td>redacted</td>
<td>4</td>
<td>0.2</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>106</td>
<td>redacted</td>
<td>5</td>
<td>0.22727272727272727</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>107</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>108</td>
<td>redacted</td>
<td>1</td>
<td>0.1</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>109</td>
<td>redacted</td>
<td>2</td>
<td>0.11764705882352941</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>110</td>
<td>redacted</td>
<td>4</td>
<td>0.13793103448275862</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>111</td>
<td>redacted</td>
<td>5</td>
<td>0.45454545454545453</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>112</td>
<td>redacted</td>
<td>-4</td>
<td>-0.5</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>113</td>
<td>redacted</td>
<td>-5</td>
<td>-0.14705882352941177</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>114</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>115</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>116</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>117</td>
<td>redacted</td>
<td>4</td>
<td>0.13333333333333333</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>118</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>119</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>120</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>121</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>122</td>
<td>redacted</td>
<td>-5</td>
<td>-0.25</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>123</td>
<td>redacted</td>
<td>2</td>
<td>0.15384615384615385</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>124</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>125</td>
<td>redacted</td>
<td>3</td>
<td>0.2727272727272727</td>
<td>4</td>
<td>
Very positive
</td>
</tr>,<tr>
<td>126</td>
<td>redacted</td>
<td>-3</td>
<td>-0.13043478260869565</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>127</td>
<td>redacted</td>
<td>0</td>
<td>0</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>128</td>
<td>redacted</td>
<td>-3</td>
<td>-0.2727272727272727</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>129</td>
<td>redacted</td>
<td>1</td>
<td>0.16666666666666666</td>
<td>3</td>
<td>
Positive
</td>
</tr>,<tr>
<td>130</td>
<td>redacted</td>
<td>-5</td>
<td>-0.7142857142857143</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>131</td>
<td>redacted</td>
<td>-3</td>
<td>-0.2</td>
<td>1</td>
<td>
Very negative
</td>
</tr>,<tr>
<td>132</td>
<td>redacted</td>
<td>4</td>
<td>0.3076923076923077</td>
<td>4</td>
<td>
Very positive
</td>
</tr>
</tbody>
</table>
</html>
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