You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task, we have Spanish and Catalan tweets for automatic stance detection. The data has three labels Against, Favor, and Neutral which express the stance towards the target -independence of Catalonia. If the tweet criticizes the independence of Catalonia then it's 'Against' and if the tweets support it then it will be labeled as 'Favor' also if the tweets state information or news  rather than stating opinion then it will be characterized as 'Neutral'.

Tweet: Vull votar i votaré.  Hi ha quelcom que no em permet no fer-ho. Ara bé tinc un greu problema.  No sé a qui!!
Solution: Favor
Why? The tweet asks for the right to vote for the independence of Catalonia and it supports the movement so it will be characterized as 'Favor'.

New input: Tweet: 📺 @BlancaBragulat:  Estic molt orgullosa. Ell esperava aquest dia per poder explicar-se   📌 Entrevista al @Mes_324   📲 Recupera l'entrevista sencera aquí ➡️ https://t.co/rDaD7t5xqv https://t.co/VSCppGhPM9
Solution:

Show your work and conclude with the exact phrasing "Therefore, the final answer is [answer]." where [answer] is just the final number or expression that solves the problem.
user
Against