- Who will be impacted? Who were sampled? Who were over sampled or under sampled? Who were the data scientists (yourself and your collaborators)? –The general audience. The presidential candidates were sampled. None of them were over or under sampled.
- What are the social and cultural impacts? What are the concerns about data privacy, security, and fairness? – This will make neutral audience to make sides. Coming to fairness there will not be any influence and since we are collecting data from Twitter which is a public domain platform there is security concerns.
- When will the social and cultural impacts take place? When should people be concerned about data privacy, security, and fairness? –Right before elections to know what people are thinking about both the candidates and after the election what people are thinking about the president.
- Where will the social and cultural impacts take place? Where will data privacy, security, and fairness issues, like data breach, and evaluative bias, likely to happen? –The social and cultural impact takes at the place of the candidates on whom the data is collected. There will be no data breach and it is unlikely to happen.
- Why are the social and cultural impacts important or consequential to the people and/or the community? Why should we be concerned about data privacy, security, and fairness issues? – These impacts are consequential to the people to refrain themselves from influential media and people around them.
- How can we address these societal issues in ML using a community-in-the-loop approach? –We can collect the data and perform NLP tasks to do the sentiment analysis