DATA4500 Social Media Analytics

...On Twitter, Trump’s 82.4 million followers dwarf Biden’s 6.4 million. The president has spent years cultivating a ragtag digital “army” of meme makers and political influencers who retweet campaign messages hundreds of times daily. ... Biden and his allies are now working feverishly to establish a social media force of their own.

For the first time, Biden outspent Trump on Facebook advertising in June, pouring twice as much money into the platform as the president. His campaign is recruiting Instagram supporters to hold virtual fundraisers.

...But Trump’s unimpeded access to the digital microphone is facing its limits.

Twitter is beginning to fact check Trump’s posts, including one that made unfounded claims that mail-in voting would lead to fraud. The company also alerted users when the president posted a manipulated video, and it hid his Twitter threat about shooting looters in Minneapolis.

...“If you want to compare the attention and engagement metrics, it might look like Trump is way ahead, but that attention and outrage isn’t always good,” Mercieca said. “When a child is throwing a tantrum, you’re giving them attention, but it’s not because you approve of their behavior.”

Indeed, the Biden campaign argues that despite being outmatched on social media, their engagement is strong.

“The way that they treat their supporters, it’s about distraction. It’s about keeping them angry,” said Rob Friedlander, Biden campaign digital director. “For us it’s about, how do we make you feel like you’re brought into the campaign.”...

Activity 2: Individual Case

Using examples from the articles above, and the sentiment analysis lectures, discuss how sentiment analysis can give your candidate’s election campaign a competitive edge.Discuss how sentiment analysis can be used to support your candidate’s campaign and undermine your opponent’s campaign.

Place your response in the space below:

Sentiment analysis is the important tool which helps to understand the inclination of people’s opininon, here in the election campaign by using sentiment analysis we can understand the contextual polarity of the american public. The sentiment analysis has three parts, positive, negative and neutral. If we check the sentiment analyzed data then we can see that around 42 % are positive tweets for Donald trump and only 9% are negative for him, if we look for other opponents then we can see that for them positive tweets are less than donald trump, in this way we can predict by using sentiment score for whom the public is positive and wants their leader. By looking this data it is very usefull in election campaign, based on it candidates can decide their further moves and includes more points in campaign which can attract more people. Also by understanding the negative scores candidates can understand that the points which he/she has kept in election manifesto are not much liked by the people hence they can remove them and new points. For example for donald trump the sentiment analysis shows positive inclination which implies public of america is liking the points which he has put up for the people.

 Data / Insights Mining 200 words)

Using examples from the articles above, and the insights mining lectures, discuss how data and insights mining can give your candidate’s election campaign a competitive edge.Discuss how data and insights mining can help to identify trends and characteristics that may escape the attention and awareness of human analysts.

Place your response in the space below:

Data mining is the cuting edge tool to predict the elections polls, the data can be extracted from the tweets and that data can be used to perform analysis by the help of data mining. The graphs and predictions can be done and predictive data can be extracted from it. Here in the context of american election campaign data mining technique is used to perform the sentiment analysis based on the tweets which user has tweeted for the candidates, from these tweets the polarity is extracted by using the NLP and according to the polarity we can predict the election results. The positive polarity is high for donald trump and which seems that the donald trump has gained much popularity during his campaign. If we look for the negative polarity than jeb bush has highest number of tweets which has negative polarity hence it suggest that the Jeb bush is least popular among his campaign and in election polls we can say that jeb bush is trailing in the election. Also by understanding the negative scores candidates can understand that the points which he/she has kept in election manifesto are not much liked by the people hence they can remove them and new points. For example for donald trump the sentiment analysis shows positive inclination which implies public of america is liking the points which he has put up for the people.

Your firm has been engaged to develop a tweet-bot for your client - either Hillary or Trump. The tweet bot will data mine tweets associated with your candidate, their opponent and everyone else who engages with these people in the form of likes, mentions, retweets and replies.The tweet bot will then use natural language processing and latent semantic analysis to learn the way your candidate ‘speaks’. Once trained, the tweet bot will tweet on your client’s behalf so that it sounds like the tweet came from the candidate.

Discuss the ethical considerations involved in the development of this bot. Your response need to address the Laws of Robotics outlined in the Appendix (see last page)

Following are the ethical consideration involved in the bot development: 1) The first and primary ethical consideration is that the bot must obey the modern robotics laws which make sure that the bot must not harm the humans in any form. 2) If the bot perfrom any kind of violation to the user then there will be direct path for user to report the abuse corresponding to the bot. 3) The important consideration must be that the bot should not impersonate the candidate rather it must specify that the user is interacting with the bot. 4) Bot should specify clearly that the data is being shared and will be used for analysis purpose. 5) The bot must respect the user and should not abuse or respond to the abuse from user, hence it obey all the rules and not harm the human in any way. 6) There will be failure transparency where any harm created by bot then there will be tracebility of it. 7) The bot will have neutral opinion and it just represent the interaction between the candidate and the user who is using the bot.

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