This limitation makes it difficult for those trying to extract trending topics from the whole data stream. It is relevant, however, that although Twitter is assumed to classify trends according to every tweet published during a period, it only provides (via its API) a reduced sample of the entire stream for free. Many users consider something to be news when it becomes a Twitter trending topic, even though the way Twitter produces these lists of trending topics is unknown, as the algorithm used remains unpublished. In fact, Twitter continuously publishes real-time produced lists of the most popular topics under discussion either locally or globally (also known as trending topics). With the advent of Twitter, public opinion can be tracked continuously and in real time. To be able to accurately track opinion over time has been one of the main concerns of analysts for a long time. This prominence of the use of Twitter for politics, the interest that the study of political information awakens, and the rising concerns about the effect of false stories (or “fake news”) on social media are what inspired us to apply our model to the analysis of political discussions during the Spanish general elections as a use case, which will be further detailed in Section 4. Besides, politically engaged young people integrate social media use into their existing organizations and political communications. This behavior is especially evident in Twitter opinion leaders, who consistently show a higher involvement in political processes. The fact is that two-thirds of social media users show some kind of political engagement by, for instance, following candidates, posting thoughts about political issues, or pressing friends to vote. In fact, literature on the use of Twitter for political activities abound, such as those studies on the effect of social media, especially Twitter, as a facilitator in political campaigns and protests worldwide. It is well known that political information is one of the most shared types of information on social media. Although our case study involves the method being applied to the political discussions held during the Spanish general, local, and European elections of April/May 2019, the method is equally applicable to many other contexts, such as sporting events, marketing campaigns, or health crises. Our approach consists of dynamically and automatically monitoring the hottest topics among all the conversations where the authorities are involved, and retrieving the tweets in connection with those topics, filtering other conversations out. Inspired by the fact that a large part of users use Twitter to communicate or receive political information, we created a method that allows for the monitoring of a set of users (which we will call authorities) and the tracking of the information published by them about an event. Unfortunately, the extraction of relevant information from the opinions that users freely express in Twitter is complicated, both because of the volume generated-more than 6000 tweets per second-and the difficulties related to filtering out only what is pertinent to our research. The literature is full of examples where Twitter is accessed, and data are downloaded as the previous step to a more in-depth analysis in a wide variety of knowledge areas. One final tip: double-check your speed limiter control, and if it’s not set correctly, don’t forget to map it to 80km/h with the appropriate button on the steering to avoid receiving a penalty for speeding in the pits.Twitter is undoubtedly one of the most widely used data sources to analyze human communication.
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