138 lines
4.8 KiB
Python
138 lines
4.8 KiB
Python
"""
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Hedonodon toot sentiment analyzer.
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This programm fetches toots from the fedihum.org Mastodon instance, calculates
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the frequencies of the sentiments (positive, neutral, negative) and the mean
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from these nominal values (even this is not statistical correct (;-_-)!, but
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not all analyzer return compounds).
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It also calculates the word count of the nouns per sentiment.
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It uses germansentiment for german toots, twitter-roberta-base-sentiment for
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english toots, and vaderSentiment for other languages.
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For the word counts I translate the toots to english with the GoogleTranslator
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first.
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"""
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from CRUDManager import CRUDManager, calculateSentimentCount, calculateSentimentMean, getYesterdaysToots
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from datetime import datetime, date
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from DbSetup import init_db
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import locale
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from MastodonAccountManager import MastodonAccountManager
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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from TootCrawler import TootCrawler
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from SentiTooter import translateToots, createWordFrequenciesPerSentiment
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locale.setlocale(locale.LC_TIME, "en_US.UTF-8")
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init_db()
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print('Initialize Mastodon...')
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mastodonAccountManager = MastodonAccountManager()
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mastodonInstance = mastodonAccountManager.instance
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"""
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mastodonInstance.log_in(
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'USER-EMAIL',
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'PW',
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to_file = 'hedonodon_usercred.secret'
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)
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"""
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print('done!')
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print('Fetching recent toots...')
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tootCrawler = TootCrawler(mastodonInstance)
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crudManager = CRUDManager()
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lastTootId = crudManager.getLastToot()
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tootsDataframe = tootCrawler.buildTootsDataframe(lastTootId)
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print('done!')
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print('Save toots to database...')
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if not tootsDataframe.empty:
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crudManager.saveToDatabase(tootsDataframe, 'Toots', useIndex=False)
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print('done!')
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else:
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print('nothing changed since last database insert!')
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print('Calculate word counts...')
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yesterdaysToots = getYesterdaysToots()
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translatedToots = translateToots(yesterdaysToots)
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wordCountsPerSentiment = createWordFrequenciesPerSentiment(translatedToots)
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print('done!')
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print(wordCountsPerSentiment);
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print('Calculate sentiment counts...')
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sentimentsYesterday = calculateSentimentCount()
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print('done!')
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print('Calculate sentiment mean...')
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sentimentMeansYesterday = calculateSentimentMean(sentimentsYesterday)
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print('done!')
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print('Save calculations to database...')
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if not tootsDataframe.empty:
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crudManager.saveToDatabase(dataframe=sentimentsYesterday, table='SentimentCounts', useIndex=True)
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crudManager.saveToDatabase(dataframe=sentimentMeansYesterday, table='SentimentMeans', useIndex=True)
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print('done!')
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else:
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print('nothing changed since last database insert!')
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print('Create figure...')
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colormap = {
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'negative': '#ff9999',
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'neutral': '#ffcc99',
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"positive": '#99ff99'
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}
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todaysColors = []
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for sentiment in sentimentsYesterday['sentiment'].to_numpy():
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todaysColors.append(colormap[sentiment])
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TodayDate = datetime.strptime(sentimentsYesterday['date'][0], '%Y-%m-%d').strftime('%d.%m.%Y')
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dataframe4PieChart = sentimentsYesterday.drop('date', axis=1).set_index('sentiment')
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dataframe4LineChart = crudManager.loadFromDatabase('SentimentMeans', 'date').drop('index', axis=1)
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fig, axes = plt.subplots(nrows=2, ncols=1, figsize=(10, 10))
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# Pie chart.
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pieChartlabels = dataframe4PieChart.index.to_numpy()
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pieChart = dataframe4PieChart.plot.pie(
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ax=axes[0],
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y='sentimentCount',
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ylabel="",
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labels=dataframe4PieChart['sentimentCount'],
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title=f'Moods of the toots on {TodayDate} of the local timeline on fedihum.org',
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colors=todaysColors,
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wedgeprops=dict(linewidth=3, edgecolor='w'),
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startangle=90
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)
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axes[0].axis('equal')
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centre_circle = plt.Circle((0, 0), 0.6, fc='white')
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axes[0].add_patch(centre_circle)
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chartBox = axes[0].get_position()
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axes[0].legend(pieChartlabels, loc='upper right', bbox_to_anchor=(0.9, 0.9))
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# Line chart.
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lineChart = dataframe4LineChart.plot.line(
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ax=axes[1],
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title='"Mean" of sentiments, calculated from nominal values, pos(1), neu (0), neg (-1)!'
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)
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axes[1].grid(True)
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axes[1].set_xlim([date(2023, 1, 1), date(2023, 12, 31)])
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axes[1].set_ylim([-1, 1])
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axes[1].xaxis.set_major_locator(mdates.MonthLocator())
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axes[1].xaxis.set_minor_locator(mdates.MonthLocator(bymonthday=15))
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axes[1].xaxis.set_major_formatter(plt.NullFormatter())
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axes[1].xaxis.set_minor_formatter(mdates.DateFormatter('%h'))
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axes[1].tick_params(which='minor', length=0)
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plotFileUrl = f'./plots/{TodayDate}.png'
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plt.savefig(plotFileUrl)
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print('done!')
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print('Send toot...')
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#media = mastodonInstance.media_post(plotFileUrl, mime_type="image/png", description=f"Sentiment analysis of local timeline on fedihum.org, showing the moods of the toots on, and the sentiment mean up to {TodayDate}.")
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#mastodonInstance.status_post(f'The moods of the toots on and up to {TodayDate}.\nWord counts per sentiment:\n{wordCountsPerSentiment}', media_ids=media, language='en')
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print('done!')
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