Assessing Sentiment of the Expressed Stance on Social Media
Table 1: Number of tweets for each topic.
['[BOLD] SemEval stance Atheism (A)', '# 733', '[BOLD] CD stance Antisemitic (AS)', '# 1050']
We study the sentiment nature in the expressed stance. To accomplish this, we used SemEval stance dataset which contains about 4000 tweets on five topics, including Atheism (A), Climate Change (CC), the Feminist Movement (FM), Hillary Clinton (HC) and the Legalisation of Abortion (LA). Furthermore, we designed a context-dependent (CD) stance dataset that contains 6324 reply tweets covering four controversial topics: Antisemitic (AS), Gender (G), Immigration (I), LGBTQ (L). We used the same annotations guideline of SemEval stance dataset [mohammad_semeval-2016_2016]. Since CD dataset is all reply tweets, the parent tweet along with reply tweet has been provided to the annotators to understand the context of the conversation to better judge the sentiment and stance.