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1{
2 "cells": [
3 {
4 "cell_type": "markdown",
5 "metadata": {},
6 "source": [
7 "# Sentiment analysis of Guardian World News articles"
8 ]
9 },
10 {
11 "cell_type": "markdown",
12 "metadata": {},
13 "source": [
14 "## Get articles from a website"
15 ]
16 },
17 {
18 "cell_type": "markdown",
19 "metadata": {},
20 "source": [
21 "### Install rss parser dependency"
22 ]
23 },
24 {
25 "cell_type": "code",
26 "execution_count": null,
27 "metadata": {},
28 "outputs": [],
29 "source": [
30 "!pip3 install feedparser"
31 ]
32 },
33 {
34 "cell_type": "markdown",
35 "metadata": {},
36 "source": [
37 "### Parsing RSS feed for world news"
38 ]
39 },
40 {
41 "cell_type": "code",
42 "execution_count": null,
43 "metadata": {},
44 "outputs": [],
45 "source": [
46 "import feedparser\n",
47 "feed_url = \"https://www.theguardian.com/world/rss\"\n",
48 "feed = feedparser.parse(feed_url)"
49 ]
50 },
51 {
52 "cell_type": "code",
53 "execution_count": null,
54 "metadata": {},
55 "outputs": [],
56 "source": [
57 "import re\n",
58 "for item in feed.entries:\n",
59 " # sanitize html\n",
60 " item.description = re.sub('<[^<]+?>', '', item.description)"
61 ]
62 },
63 {
64 "cell_type": "markdown",
65 "metadata": {},
66 "source": [
67 "### Install Vader Sentiment library and perform sentiment analysis"
68 ]
69 },
70 {
71 "cell_type": "code",
72 "execution_count": null,
73 "metadata": {},
74 "outputs": [],
75 "source": [
76 "!pip3 install vaderSentiment"
77 ]
78 },
79 {
80 "cell_type": "code",
81 "execution_count": null,
82 "metadata": {},
83 "outputs": [],
84 "source": [
85 "from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer\n",
86 "analyser = SentimentIntensityAnalyzer()"
87 ]
88 },
89 {
90 "cell_type": "code",
91 "execution_count": null,
92 "metadata": {},
93 "outputs": [],
94 "source": [
95 "sentiment_results = []\n",
96 "for item in feed.entries:\n",
97 " sentiment_title = analyser.polarity_scores(item.title)\n",
98 " sentiment_description = analyser.polarity_scores(item.description)\n",
99 " sentiment_results.append([sentiment_title['compound'], sentiment_description['compound']])"
100 ]
101 },
102 {
103 "cell_type": "markdown",
104 "metadata": {},
105 "source": [
106 "### Install Matplotlib and visualize compound score"
107 ]
108 },
109 {
110 "cell_type": "code",
111 "execution_count": null,
112 "metadata": {},
113 "outputs": [],
114 "source": [
115 "!pip3 install matplotlib"
116 ]
117 },
118 {
119 "cell_type": "code",
120 "execution_count": null,
121 "metadata": {},
122 "outputs": [],
123 "source": [
124 "import matplotlib.pyplot as plt"
125 ]
126 },
127 {
128 "cell_type": "code",
129 "execution_count": null,
130 "metadata": {},
131 "outputs": [],
132 "source": [
133 "%matplotlib inline\n",
134 "plt.rcParams['figure.figsize'] = (15, 3)\n",
135 "plt.plot(sentiment_results, drawstyle='steps')\n",
136 "plt.title('Sentiment analysis relationship between title and description (Guardian World News)')\n",
137 "plt.legend(['title', 'description'])\n",
138 "plt.show()"
139 ]
140 },
141 {
142 "cell_type": "code",
143 "execution_count": null,
144 "metadata": {},
145 "outputs": [],
146 "source": []
147 }
148 ],
149 "metadata": {
150 "kernelspec": {
151 "display_name": "Python 3",
152 "language": "python",
153 "name": "python3"
154 },
155 "language_info": {
156 "codemirror_mode": {
157 "name": "ipython",
158 "version": 3
159 },
160 "file_extension": ".py",
161 "mimetype": "text/x-python",
162 "name": "python",
163 "nbconvert_exporter": "python",
164 "pygments_lexer": "ipython3",
165 "version": "3.7.3"
166 }
167 },
168 "nbformat": 4,
169 "nbformat_minor": 4
170}