Mining Public Opinion about Economic Issues: Twitter and the U.S. Presidential Election

Opinion polls have been the bridge between public opinion and politicians in elections. However, developing surveys to disclose people's feedback with respect to economic issues is limited, expensive, and time-consuming. In recent years, social media such as Twitter has enabled people to share their opinions regarding elections. Social media has provided a platform for collecting a large amount of social media data. This paper proposes a computational public opinion mining approach to explore the discussion of economic issues in social media during an election. Current related studies use text mining methods independently for election analysis and election prediction; this research combines two text mining methods: sentiment analysis and topic modeling. The proposed approach has effectively been deployed on millions of tweets to analyze economic concerns of people during the 2012 US presidential election

Social Media Would Not Lie: Prediction of the 2016 Taiwan Election via Online Heterogeneous Data

The prevalence of online media has attracted researchers from various domains to explore human behavior and make interesting predictions. In this research, we leverage heterogeneous social media data collected from various online platforms to predict Taiwan's 2016 presidential election. In contrast to most existing research, we take a "signal" view of heterogeneous information and adopt the Kalman filter to fuse multiple signals into daily vote predictions for the candidates. We also consider events that influenced the election in a quantitative manner based on the so-called event study model that originated in the field of financial research. We obtained the following interesting findings. First, public opinions in online media dominate traditional polls in Taiwan election prediction in terms of both predictive power and timeliness. But offline polls can still function on alleviating the sample bias of online opinions. Second, although online signals converge as election day approaches, the simple Facebook "Like" is consistently the strongest indicator of the election result. Third, most influential events have a strong connection to cross-strait relations, and the Chou Tzu-yu flag incident followed by the apology video one day before the election increased the vote share of Tsai Ing-Wen by 3.66%. This research justifies the predictive power of online media in politics and the advantages of information fusion. The combined use of the Kalman filter and the event study method contributes to the data-driven political analytics paradigm for both prediction and attribution purposes

Novel weapons: the invasion of fake news and the evolution of political news ecosystems

In this dissertation, I work to answer the question: how are recent attempts to insert fake news into political news ecosystems similar to and different from previous attempts? To this end, I present a historical timeline of major technological shifts that have altered political news ecosystems, create a new framework for analyzing how fake news producers use social media as a novel weapon to help fake news invade and thrive within political news ecosystems, and develop new terminology to discuss large-scale trolling tactics used to disrupt political news ecosystems. To develop the novel weapons framework for this study, I first identify and then examine three aspects of social media that are reappropriated to transform it into a novel weapon: hashtags, bots, and trolling. Then, I unpack how fake news producers and disseminators leveraged hashtags, bots, and trolling in tandem to create more complex systems that were able to introduce and disseminate fake news that went relatively unnoticed by the general public. From here, I enact this framework, applying it to the fake news surrounding the school shooting in Parkland, Florida. In doing so, I demonstrate that the novel weapons framework is easily applicable and able to provide an analytical depiction not only of the initial infiltration of fake news into a political news ecosystem but also the tactics that are used to help it thrive. My recalibration of the novel weapons framework aims to expand ecology theory in the field of Rhetoric and Composition by adapting invasive species theory and the novel weapons hypothesis to create a lens through which we can analyze how new actors or agents enter and manipulate digital ecologies. However, rather than focus on individual actors circulating fake news, this framework allows us to identify and focus on the systemic and ecological invasion of fake news.. Additionally, this framework provides a historical lens with which one can observe or analyze how the invasive species’ role or relationship with the ecosystem fluctuates over time. Lastly, through the development of the novel weapons framework, I developed new terminology in order to differentiate between the umbrella term of troll and the large entities that use trolling tactics for much higher stakes. In this dissertation, such bad actors and tactics are referred to as organized, agenda-driven, strategic trolls or OASTs. By separating entities like foreign governments and politically affiliated organizations that use trolling tactics from the colloquial term troll, I also separates them from the stereotypes and cultural frameworks that view trolls as minimal threats, annoyances, singular people, or subversive tactics to oppressive and bigoted language and ideologies. Creating this distinction allows us to focus on the more complex levels and higher stakes that are involved when dealing with OASTs. This new terminology now fits the impact that these entities can create. Overall, then, this dissertation develops a new framework for studying and analyzing fake news, the expansion of terminology when discussing trolls, and the practical application of the novel weapons framework.Thesis (Ph. D.

Noncooperative dynamics in election interference

Foreign power interference in domestic elections is an existential threat to societies. Manifested through myriad methods from war to words, such interference is a timely example of strategic interaction between economic and political agents. We model this interaction between rational game players as a continuous-time differential game, constructing an analytical model of this competition with a variety of payoff structures. All-or-nothing attitudes by only one player regarding the outcome of the game lead to an arms race in which both countries spend increasing amounts on interference and counterinterference operations. We then confront our model with data pertaining to the Russian interference in the 2016 United States presidential election contest. We introduce and estimate a Bayesian structural time-series model of election polls and social media posts by Russian Twitter troll accounts. Our analytical model, while purposefully abstract and simple, adequately captures many temporal characteristics of the election and social media activity. We close with a discussion of our model\u27s shortcomings and suggestions for future research

Decrypting Democracy: Incentivizing Blockchain Voting Technology for an Improved Election System

[B]lockchain technology provides a cryptographically secure and transparent method for transferring “digital assets.” Although blockchain technology is most commonly recognized as the technology that underpins virtual currencies, such as Bitcoin, it may also hold the key to facilitating secure online elections in America. To preface the need for blockchain voting, Part II addresses the current problems with voting in the United States. Part III provides an elementary explanation of blockchain. Parts IV and V outline current election laws and explain how implementing blockchain voting would very likely comply with these laws. Transitioning to a new voting system, however, does not come without challenges. Thus, the remainder of Part V outlines valid concerns with and counterarguments against blockchain voting. Part VI advocates for congressional action, tracing the failed regulation of Bitcoin back to the lack of uniform guidance. The time is ripe for modernization, yet current proposals for online voting lack the sophistication necessary to implement a secure and trusted system. Thus, Part VII of this Comment proposes that Congress pass a bill authorizing the use of blockchain voting and incentivizing states to modernize voting systems using this innovative technology