Do the political opinions shared on Social Media (platform Twitter) accurately represent the political opinions of the general populace? (original) (raw)

Every tweet counts? How sentiment analysis of social media can improve our knowledge of citizens' political preferences with an application to Italy and France

New Media & Society, 2014

ABSTRACT The growing usage of social media by a wider audience of citizens sharply increases the possibility of investigating the web as a device to explore and track political preferences. In the present paper we apply a method recently proposed by other social scientists to three different scenarios, by analyzing on one side the online popularity of Italian political leaders throughout 2011, and on the other the voting intention of French Internet users in both the 2012 presidential ballot and the subsequent legislative election. While Internet users are not necessarily representative of the whole population of a country’s citizens, our analysis shows a remarkable ability for social media to forecast electoral results, as well as a noteworthy correlation between social media and the results of traditional mass surveys. We also illustrate that the predictive ability of social media analysis strengthens as the number of citizens expressing their opinion online increases, provided that the citizens act consistently on these opinions.

Social media discourse and voting decisions influence: sentiment analysis in tweets during an electoral period

Social Network Analysis and Mining

In a time where social media is fundamental for any political campaign and to share a message with an electoral audience, this study searches for a conclusion of the actual persuasion capacity of social media in the electors when they need to decide whom to vote for as their next government. For this, it compares the sentiment that Social Media users demonstrated during an electoral period with the actual results of those elections. For this analysis, it was used, as a case study, tweets mentioning the two major English parties, Conservative and Labor, their respective candidates for the position of prime minister, and terms that identified their political campaign during the electoral period of the General Elections of the United Kingdom that occurred on December 12, 2019. Data were collected using R. The treatment and analysis were done with R and RapidMiner. Results show that tweets’ sentiment is not a reliable election results predictor. Additionally, results also show that it i...

A Twitter Sentiment Gold Standard for the Brexit Referendum

Proceedings of the 12th International Conference on Semantic Systems - SEMANTiCS 2016, 2016

In this paper, we present a sentiment-annotated Twitter gold standard for the Brexit referendum. The data set consists of 2,000 Twitter messages ("tweets") annotated with information about the sentiment expressed, the strength of the sentiment, and context dependence. This is a valuable resource for social media-based opinion mining in the context of political events. CCS Concepts • Computing methodologies➝Artificial intelligence➝Natural language processing➝Language resources.

Comparing Sentiment Analysis from Social Media Platforms – Insights and Implications

Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI - 2019), 2020

The ubiquitous presence of social media is exerting its influence on several institutions in society by both positive and negative ways. In this context it behooves researchers to understand the validity of the influence of social media and what it means to the functionality of the institutions in society which include healthcare, politics, education, marriage, etc. This paper presents results and insights obtained from comparing sentiment analysis applied to Twitter and YouTube data on a set of topics. The focus of this study was to observe differences among sentiments expressed on different social media platforms. In other words, was there any influence generated by the social media platform on the individual's expression of sentiments. Additionally, we also developed an app to encourage citizen data scientists to search for a topic relevant to their area of interest and obtain sentiment analysis for that topic.

Inferring Political Preferences from Twitter

ArXiv, 2020

Sentiment analysis is the task of automatic analysis of opinions and emotions of users towards an entity or some aspect of that entity. Political Sentiment Analysis of social media helps the political strategists to scrutinize the performance of a party or candidate and improvise their weaknesses far before the actual elections. During the time of elections, the social networks get flooded with blogs, chats, debates and discussions about the prospects of political parties and politicians. The amount of data generated is much large to study, analyze and draw inferences using the latest techniques. Twitter is one of the most popular social media platforms enables us to perform domain-specific data preparation. In this work, we chose to identify the inclination of political opinions present in Tweets by modelling it as a text classification problem using classical machine learning. The tweets related to the Delhi Elections in 2020 are extracted and employed for the task. Among the seve...

Echo Chamber or Public Sphere? Predicting political orientation and measuring political homophily in Twitter using big data.

Journal of Communication, 64(2): 317-332., 2014

This paper investigates political homophily on Twitter. Using a combination of machine learning and social network analysis we classify users as Democrats or Republicans based on the political content shared. We then investigate political homophily both in the network of reciprocated and non reciprocated ties. We find that structures of political homophily differ strongly between Democrats and Republicans. In general Democrats exhibit higher levels of political homophily.

Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment

In this paper we report research results investigating microblogging as a form of electronic word-of-mouth for sharing consumer opinions concerning brands. We analyzed more than 150,000 microblog postings containing branding comments, sentiments, and opinions. We investigated the overall structure of these microblog postings, the types of expressions, and the movement in positive or negative sentiment. We compared automated methods of classifying sentiment in these microblogs with manual coding. Using a case study approach, we analyzed the range, frequency, timing, and content of tweets in a corporate account. Our research findings show that 19% of microblogs contain mention of a brand. Of the branding microblogs, nearly 20% contained some expression of brand sentiments. Of these, more than 50% were positive and 33% were critical of the company or product. Our comparison of automated and manual coding showed no significant differences between the two approaches. In analyzing microblogs for structure and composition, the linguistic structure of tweets approximate the linguistic patterns of natural language expressions. We find that microblogging is an online tool for customer word of mouth communications and discuss the implications for corporations using microblogging as part of their overall marketing strategy.

Revisiting The American Voter on Twitter

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

The American Voter-a seminal work in political scienceuncovered the multifaceted nature of voting behavior which has been corroborated in electoral research for decades since. In this paper, we leverage The American Voter as an analysis framework in the realm of computational political science, employing the factors of party, personality, and policy to structure the analysis of public discourse on online social media during the 2016 U.S. presidential primaries. Our analysis of 50 million tweets reveals the continuing importance of these three factors; our understanding is also enriched by the application of sentiment analysis techniques. The overwhelmingly negative sentiment of conversations surrounding 10 major presidential candidates reveals more "crosstalk" from Democratic leaning users towards Republican candidates, and less vice-versa. We uncover the lack of moderation as the most discussed personality dimension during this campaign season, as the political field becomes more extreme-Clinton and Rubio are perceived as moderate, while Trump, Sanders, and Cruz are not. While the most discussed issues are foreign policy and immigration, Republicans tweet more about abortion than Democrats who tweet more about gay rights than Republicans. Finally, we illustrate the importance of multifaceted political discourse analysis by applying regression to quantify the impact of party, personality, and policy on national polls.

Mapping Twitter's information sphere in the lead-up to the Brexit Referendum: How Eurosceptic views outpaced their rivals

AoIR

Short Abstract How did Eurosceptic (Leave) and pro-European (Remain) activity compare on social media in the run-up to the EU referendum, what kind of information did users share, and did this confine the two camps to informational echo chambers? To answer these questions we collected more than 7.5 million Brexit-related tweets through Twitter's streaming API. We enriched our data using a support vector machine to identify which tweets clearly supported the Leave or Remain camp, mapped twitter users within our data to the location specified in their user profile, and mined URLs shared in tweets. We find that Leave users were more numerous, and individually more active in tweeting to support their cause. Leave users also tended to be less open, and more engaged within their own echo-chamber, something that is reflected in the URLs they shared. URLs pointing to Eurosceptic domains were shared more widely than those pointing to pro-European domains. Surprisingly, The Express was one of the most prominent domains shared on twitter, more than its more prominent Eurosceptic counterpart, the Daily Mail. Overall, twitter users who supported Leave appeared to be much more active and motivated in advancing their cause than Remainers were in advocating continued EU membership. The use of twitter in the Brexit campaign demonstrates how social media users pushed a hitherto marginal political agenda to the front and center of public discourse.

Political Opinion Analysis in Social Networks: Case of Twitter and Facebook

International journal of Web & Semantic Technology, 2021

The 21st century has been characterized by an increased attention to social networks. Nowadays, going 24 hours without getting in touch with them in some way has become difficult. Facebook and Twitter, these social platforms are now part of everyday life. Thus, these social networks have become important sources to be aware of frequently discussed topics or public opinions on a current issue. A lot of people write messages about current events, give their opinion on any topic and discuss social issues more and more. The emergence and enormous popularity of these social networks have led to the emergence of several types of analysis to take advantage of them. One of them is the analysis of opinions in texts. It aims at automatically classifying opinions in order to position them on a sentiment scale, thus allowing to characterize a set of opinions without having to rely on a human to read them. Currently, opinion analysis offers us a lot of information related to public opinion, eith...