Twitter Trending Topic Monitor

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Twitter has become a global platform of conversations. There are currently around 290 million active Twitter users from all over the world and they speak their mind through short messages called tweets. Every one online minute, about 575 thousand of tweets sent. These tweets are summarized in real-time by Twitter as a list of trending topics.

Twitter trending topics is a list of keywords that are most commonly mentioned in tweets in a given time. Twitter trending topics data are publicly accessible and are grouped based on the areas from which the tweets were originated. Beside the keywords and the region information, Twitter trending topics data also contain the approximate number of tweets that contain the respective keyword(s).

Twitter trending topics data can provide useful insights about popular issues and conversations among the people of the world. This is why we built the Twitter Trending Topic Monitor data dashboard. The dashboard is intended to help viewers track the popular topics in Twitter tweets. The dashboard also tracks the pattern of trending topic’s progression in time terms of tweet volume. Such pattern can be useful in determining the urgency of the topics being discussed or even the authenticity and anomaly of the conversations.

Twitter Trending Topic Monitor tracks trending topics of eleven countries, namely Indonesia, Japan, United States, United Kingdom, Australia, Singapore, India, Russia, France, Germany, South Korea. Through the use of Twitter API, we log trending topics four times every day, specifically one in the morning, noon, evening, and night in Indonesia time (GMT / UTC +7). The logging time were made to be as evenly distributed as possible during the whole day, although this may often not be the case. The time information presented in the dashboard are all in GMT. The trending topic keywords visualized in the data were limited to keywords with tweet volume of over ten thousand tweets.

We present the Twitter trending topics data in six visualizations. Those six visualizations are:
+ Trending topic word cloud based on median tweet volume
+ Table of trending topics
+ Median of tweet volume number
+ Tweet volume by trending topic and time line chart
+ Median tweet volume by trending topic bar chart
+ Animated tweet volume by trending topic and time scatter plot

All of the visualizations are affected by the country, time, and keyword parameters that are chosen by viewers. The viewers can select those parameters through the dropdown menu and the slider available in the dashboard. In the visualizations, median number of tweet is chosen over average number to summarize the tweet volume data. The median parameter is specifically chosen to reduce the effect of outliers in the tweet volume data.

The trending topic word cloud based on tweet volume is designed to help viewers intuitively grasp the variety of the trending topics and the popularity comparison between trending topics. The size of words ares determined by the median of tweet volume of the respective keyword among all the records where that keywords are found. Even though this word cloud can give perceptions of popularity comparison, such comparison may be more suited to be observed in another form of visualization in this dashboard, namely the bar chart.

The table of trending topics provide the textual data on which all other visualizations are based. From the table, viewers can find details of the record logging time (the date, hour, minute, and second when the data was extracted), country, trending topic keyword, and tweet volume.

The tweet volume by trending topic and time line chart presents time series chart of the trending topic keyword with respect to record logging time. The higher the location of a point in the graph, the larger the tweet volume of the keyword that the data point represents.

The animated tweet volume by trending topic and time scatter plot presents the same data as the previous time series chart, only animated. By the touch of the play button, viewers can see the trending topic data points move along the the tweet volume scale as time goes by according to the record logging time.

The median of tweet volume number gives an overview of how many tweets are being visualized in the dashboard. As with all other visualizations in the dashboard, this number changes according to the keyword, country, and time selected by the viewer. It should be noted that trending topic keywords with volume less than ten thousand tweets are excluded, so the number in this visualization (as in all of the visualizations in the dashboard) doesn’t represent all of the trending topic keywords available in the Twitter API.

The median tweet volume by trending topic bar chart visualizes the exact data as the word cloud, only in the form of bar chart. While the word cloud is intended mainly to provided an overview of trending topics diversity, the bar chart is mainly designed to give a better look on the comparison of trending topic popularity.

Twitter Trending Topic Monitor data dashboard was built using Microsoft Power BI, Python programming language, Google Colab, MySQL database, and Jupyter Notebook. We would like to express gratitude to Twitter for making their data freely accessible through the Twitter API.