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Q5
Browse files- hw2-dh500-cvargas.ipynb +42 -19
hw2-dh500-cvargas.ipynb
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"end_time": "2024-04-
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"start_time": "2024-04-
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"source": [
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"student = 'Carlos Alberto Vargas Rivera'\n",
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"
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"print(f'Author: {student} ({sciper})')"
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{
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"id": "992263206e59f051",
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"metadata": {
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"end_time": "2024-04-14T19:00:44.730100Z",
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"start_time": "2024-04-14T19:00:44.726958Z"
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"source": [
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"student, sciper = 'Carlos Alberto Vargas Rivera', '384891'\n",
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"print('Author:', f'{student} ({sciper})')"
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"execution_count": 268
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"cell_type": "markdown",
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"source": [
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"### Q5 - Discussion results of points 3 & 4\n",
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"\n",
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"Are any of the results unexpected? Why?"
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],
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"id": "3da960163cc539a"
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"source": [
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"It is interesting that even due more than the half of the Tweets contain URLS (55.7%). Then, only the 10.7% of them are re-tweets. It means that **the most of the tweets are citing or promoting sources out of the Tweeter ecosystem.**\n",
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"\n",
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"Additionally, at subsampling my *arbitrary* selected groups of MEDIA SOURCES and INFLUENCERS. One can observe similar insights as those presented in the class last Friday:\n",
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"\n",
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"- These random MEDIA SOURCES already produced ~3% of the Tweets.\n",
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"- These ~3% of Tweets are **DIRECT** Tweets. Thus, they produce them themselves.\n",
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"- The **MEDIA SOURCES** are active, but not as active as the **INFLUENCERS**. This second group produce almost the double of the Tweets (~6%).\n",
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"- **INFLUENCERS** RETWEET more than the **MEDIA SOURCES**. However, the most of their tweets are also **DIRECT**.\n",
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"- MEDIA Retweets (~0.11%) compared to INFLUENCERS retweets (~0.73%)."
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"end_time": "2024-04-14T22:55:31.509477Z",
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"start_time": "2024-04-14T22:55:31.504609Z"
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"cell_type": "code",
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"source": "print('Das is todo, merci!')",
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"id": "992263206e59f051",
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"outputs": [
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Das is todo, merci!\n"
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],
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"execution_count": null,
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"source": "",
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"id": "48a770ca733f9401"
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"metadata": {
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