Political Sentiment Research Articles

A Review on Lexicon-Based and Machine Learning Political Sentiment Analysis Using Tweets

Sentiment analysis over social media platforms has been an active case of study for more than a decade. This occurs due to the constant rising of Internet users over these platforms, as well as to the increasing interest of companies for monitoring the opinion of customers over commercial products. Most of these platforms provide free, online services such as the creation of interactive web communities, multimedia content uploading, etc. This new way of communication has affected human societies as it shaped the way by which an opinion can be expressed, sparking the era of digital revolution. One of the most profound examples of social networking platforms for opinion mining is Twitter as it is a great source for extracting news and a platform which politicians tend to use frequently. In addition to that, the character limitation per posted tweet (maximum of 280 characters) makes it easier for automated tools to extract its underlying sentiment. In this review paper, we present a variety of lexicon-based tools as well as machine learning algorithms used for sentiment extraction. Furthermore, we present additional implementations used for political sentiment analysis over Twitter as well as additional open topics. We hope the review will help readers to understand this scientifically rich area, identify best options for their work and work on open topics.

Colorado--The Changing Landscape of Land Use Law and Regulations Impacting the Colorado Oil and Gas Industry: From the Colorado Oil and Gas Conservation Act of 1951 to Senate Bill 181 of 2019

When Colorado Democratic Governor Jared Polis approved Senate Bill 181, this new law significantly redirected the historical focus of Colorado oil and gas regulation. This provided a significant delegation of land use related authority to local government for the first time since the passage of this Act in 1951. This new law moved away from the traditional notion of statewide regulation based upon exclusive jurisdiction by the Colorado Oil and Gas Conservation Commission (“COGCC”). While this change of legislative focus is significant, this latest direction is probably a natural continuation of a general trend that has been emerging in Colorado since certain Supreme Court Opinions were announced in 1992, as explained later in this Article. As the State of Colorado has, among other things, grown in population, residential housing now significantly finds itself competing with oil and gas development in the same geographical areas, especially the suburbs of the “Front Range.” Simultaneously, the political sentiment of Colorado has trended into a more significantly Democratic direction from a historically Republican majority. The law as to the governance of the oil and gas industry has now changed as a result of the passing of SB 181—from fostering the development of oil and gas industry to a new paradigm requiring the weighing of interests, including environmental concerns. This Article provides a historic explanation to allow the reader to better understand how this transition has come about. That which is observed in Colorado might also be seen as a potential harbinger of future change that could be noted in other oil and gas states.

Polarity Analysis of Dynamic Political Sentiments from Tweets with Deep Learning Method

Polarity Analysis of Dynamic Political Sentiments from Tweets with Deep Learning Method

Dynamics of social and Political Attitudes and Analysis of the Results of the Regional Elections of 2015–2019 in the Irkutsk Region

The article presents the data of the study of the dynamics of social and political attitudes and the analysis of the results of the regional elections of 2015–2019 in the Irkutsk region. In 2019, a sociological study was conducted in this region, which allowed determining the reasons for the formation of protest social and political sentiments. For the analysis, the author used the results of elections of the Governor of Irkutsk region in 2015 and results of elections of deputies of Legislative Assembly of Irkutsk region in 2018. Further, the author compared also votes to the Duma of the city of Irkutsk in 2019. The study identified features of the formation of the protest political attitude of residents of Irkutsk oblast and the trends of their impact on the election results at the regional level (protest voting). Finally, the author explained the reasons of the defeat of the last Governor Sergei Eroschenko and the victory of S. Levchenko, causes of deterioration of the results of the party “United Russia” and the victory of the Communist Party in the elections to the Legislative Assembly of the Irkutsk region in 2018.

Research on Dynamic Political Sentiment Polarity Analysis of Specific Group Twitter Based on Deep Learning Method

The article introduce a method to analyzing the dynamic political sentiment polarity of American politicians’ tweets within a fixed period of time to assist analysts in judging the direction of American politics and the future trend of China-US relations. This research is applied in the field of think tanks or intelligence analysis. The service targets are intelligent analysts, and the data is the tweet text data sent by a specific group in a fixed time period. We propose an architecture that combines multiple deep learning models and use a dedicated tweet data set to construct a specific group to obtain an sentiment polarity multi-classifier, and then introduce the time characteristics of tweets, and finally obtain the dynamic political sentiment polarity of politicians. The US politician tweets data set proposed in this article verifies that the proposed comprehensive architecture is better than traditional deep learning methods in this task, and the accuracy of the classifier verification set reaches 80.66%. According to the sentiment polarity judgments of 20 US governors and senators, the success rate is 75%. The analysis of individual dynamic political sentiment polarity can provide effective help and intelligence support for analysts. The method in this paper effectively uses a variety of deep learning techniques to assist analysts to obtain more accurate dynamic political sentiment polarity from massive Twitter text data.

If It's Heavy It's Ripe: On Writing and Political Sentiment

If It's Heavy It's Ripe: On Writing and Political Sentiment

Predicting political sentiments of voters from Twitter in multi-party contexts

Prior Twitter-based electoral research has mostly ignored multi-party contexts and ‘mix tweets’ that jointly mention more than one party. Hence, we investigate the complex nature of these mix tweets in a multi-party context, and we argue mix tweeting patterns of users implicitly capture their political opinions. We predict the political leaning of users based on their mix tweeting patterns in the context of the 2014 Indian General Election. We have agglomerated 2.4 million tweets from 0.15 million unique users. Next, we employ a multinomial logit regression model to test the hypothesized causal relation between mix tweeting patterns and the political leaning of users. Additionally, we also employ neural network-based algorithms to predict political leaning. Our study demonstrates that user-level mix-tweeting patterns can reveal the political opinions of Twitter users.

Początki ruchu komunistycznego na Górnym Śląsku (1918–1924)

The defeat of the German Empire in World War I contributed to the radicalisation of social and political sentiment in Germany. In the territory of Upper Silesia, a borderland of the German Reich, these conflicts strengthened national antagonisms. In such a situation the Communist Party of Upper Silesia was created at the end of 1918, achieving serious organisational successes and greatly influencing the attitude of a large number of industrial workers. These local communists sought to channel radical social moods into a communist revolution, but they collided with and lost to Polish and German nationalism. At the time of the decisive battle for Upper Silesia’s nationalities, the communist movement was seriously weakened and did not matter in the struggle for the future of the region. After the division of Upper Silesia in 1922, the structures of the Communist Party of Upper Silesia were incorporated on a territorial basis into the Communist Party of Germany (KPD) or the Communist Party of Poland (KPP). The communists operating in the Polish Silesia (Silesian voivodship) region managed to take advantage of mass strikes in 1923 and led to civil unrest. An attempt to escalate this tension was hindered by the pacification action carried out by state authorities. The most important activists were imprisoned and the party itself had to go underground, sharing the fate of the KPP. The communists active in the KPD also tried to lead the population of the German part of Upper Silesia into revolt but, although they were close to success several times, did not manage to channel the strike into a communist revolution. However, they remained one of the three most influential political parties in the German Upper Silesian Province.

Analysis of Political Sentiment From Twitter Data

A new method of approaching sentiment classification is proposed where the likelihood of word embeddings to produce useful information from limited Twitter data is studied. The novelty of this work is in determining how short corpuses (taken from Twitter data) are polarized to multiple axes with respect to a subject, as opposed to using a single positive-negative sentiment axis to classify the text with respect to a subject. The unique methodology of this model focuses on deconstructing a short corpus (microblogging entry from Twitter) into key tokens, identifying the correct axis of the sentiment (the polarization axis) using cosine similarity, and then using this axis to generate polarization values to classify each selection of text into fine-tuned axis values. Results of this study show that a single axis may not be enough to express a sentiment. Various axes will have to be combined for better results. Results were measured in terms of classification accuracy, classification bias, and an axis score.

Policy Change and Public Opinion: Measuring Shifting Political Sentiment With Social Media Data

This article uses Twitter data and machine-learning methods to analyze the causal impact of the Supreme Court’s legalization of same-sex marriage at the federal level in the United States on political sentiment and discourse toward gay rights. In relying on social media text data, this project constructs a large data set of expressed political opinions in the short time frame before and after the Obergefell v. Hodges decision. Due to the variation in state laws regarding the legality of same-sex marriage prior to the Supreme Court’s decision, I use a difference-in-difference estimator to show that, in those states where the Court’s ruling produced a policy change, there was relatively more negative movement in public opinion toward same-sex marriage and gay rights issues as compared with other states. This confirms previous studies that show Supreme Court decisions polarize public opinion in the short term, extends previous results by demonstrating opinion becomes relatively more negative in states where policy is overturned, and demonstrates how to use social media data to engage in causal analyses.

Exploring adjustment mechanisms of adolescent expat kids from South Asia against sociopolitical stigma

PurposeIn recent times, several instances of anti-immigration-related hate crimes and religious bullying have been reported where South Asian expatriates have been victimized. The accompanying children of such expatriates may find such hostile perceptions very difficult to deal with due to their tender age and sensitive ego, which may also lead to the premature return of the expatriate. In this study, a qualitative investigation is conducted to understand the specific problems faced by South Asian expat kids with respect to religious stigma and anti-immigration sentiments.Design/methodology/approachA latent thematic analysis was adopted as the research method in this study. Responses were obtained from 27 South Asian adolescent expat kids through audiovisual interviews.FindingsA total of three central themes were identified from the analysis: (1) coping against social stigma, (2) dealing with social isolation and (3) assimilating with host culture. The findings indicated that the expat kids from South Asia were mentally well prepared to cope with bullying related to the religious or political sentiment using several self-reflective orientations and through optimal use of technical resources.Research limitations/implicationsThis study applies a qualitative exploratory design. Hence, a follow-up study backed by quantifiable data is needed to enhance generalizability of the findings.Practical implicationsCorporate practitioners may develop dedicated social media page for expat kids or an online community of such individuals as a support system.Originality/valueThe paper applies a critical lens on some deep-rooted sociopolitical issues which have not been addressed in extant literature on expat adjustment.

"O rio da secura deságua na guerra”

A cidade do Rio de Janeiro, ao tornar-se palco de diversos Grandes Eventos, foi apresentada como uma marca, a “Rio2016”, cujo slogan oficial é “A New World”, o que revela a opção pela adequação às diretrizes do mundo globalizado a partir do “norte”, que encara as cidades enquanto commodities, mercadorias (Vainer, 2000). Neste dito new world, a ideia da integração entre as forças de segurança/controle e o aprimoramento do Sistema Integrado de Comando e Controle (SICC), surge como um dos maiores legados e se materializa no Centro Integrado de Comando e Controle (CICC), prédio-sede para a desejada articulação das forças de segurança atuantes na cidade que se responsabilizariam pela garantia dos espetáculos em questão. Passados os eventos, anuncia-se uma nova grande crise no campo da segurança pública e no CICC se instala o gabinete da intervenção federal militar, solução política-institucional adotada para a referida crise. Utilizamos aqui, portanto, o CICC como uma linha de percurso analítico e simbólico para construirmos um arco narrativo sobre a passagem dos Grandes Eventos à decretação da intervenção, com foco nas problemáticas do campo da segurança pública, com destaque para os discursos das autoridades referentes e a instrumentalização de dados sobre a crise. Valemo-nos, por exemplo, das contribuições de Stephen Graham (2016) sobre o “novo urbanismo militar”, de Bruno Cardoso (2014) sobre o próprio CICC e de Vera Malaguti sobre a cidade do Rio e seus sentimentos políticos, principalmente o medo (2003).

Egyptian foreign policy after the 2011 revolution: the dynamics of continuity and change

ABSTRACT The outbreak of the Egyptian 2011 revolution raised expectations in academic and policy-oriented circles that Egypt would chart a new foreign policy discourse in response to the demands of its revolutionary public and the competing political forces that sought to shape its power. This article examines the development of Egyptian foreign policy after the 2011 revolution, with a view of identifying the patterns of continuity and change and their primary underlying causes. The article contends that, contrary to expectations, the elements of continuity were far more powerful than propensities for change during period of SCAF and Morsi where the revolutionary sentiment in Egyptian politics was at its peak. While the rise of Sisi to power seemed to have ended the revolutionary zeal in contemporary Egypt, it was only then that Egypt’s foreign policy has witnessed the most relatively significant change in the last 40 years.

Analysis of Parliamentary Debate Transcripts Using Community-Based Graphical Approaches (Student Abstract)

Gauging political sentiments and analyzing stances of elected representatives pose an important challenge today, and one with wide-ranging ramifications. Community-based analysis of parliamentary debate sentiments could pave a way for better insights into the political happenings of a nation and help in keeping the voters informed. Such analysis could be given another dimension by studying the underlying connections and networks in such data. We present a sentiment classification method for UK Parliament debate transcripts, which is a combination of a graphical method based on DeepWalk embeddings and text-based analytical methods. We also present proof for our hypothesis that parliamentarians with similar voting patterns tend to deliver similar speeches. We also provide some further avenues and future work towards the end.

Crisis, Otherness, Positionality: Thinking Beyond ‘Self and Other’ in Turbulent Times

‘The new walls of Europe reflect crises in Europe’s relation to itself and the world’ (Wendy Brown, Walled States, Waning Sovereignty, preface to the 2017 edition). In Germany, Austria and Switzerland, as elsewhere, populism has been on the rise, and far-right discourse has altered the political landscape. Should we respond with a re-thinking of community or is ‘community’ itself part of the problem? Can an ethics of alterity (which we find in Levinas) help re-define what we understand by community? As early as 1924, in Grenzen der Gemeinschaft, Helmuth Plessner warned that ‘too much’ community, far from being positive in an egalitarian sense, can foster aggressive identity-based ‘us-versus-them’ political sentiment. Plessner, in his major work, Die Stufen des Organischen und der Mensch (1928) develops his idea of ‘positionality’ and what we might describe as looking at human beings as ‘in-between’ creatures, bordering on other animals, connected to each other socially, culturally, politically, but also separate. Plessner is searching for a new way of looking at ‘borders’ — boundaries between connectedness and separation. Almost one hundred years after Plessner’s publications, I will argue that they still offer a valuable perspective on the theme of ‘border’ and one which may help counter the aggressiveness of contemporary western discourse on borders. In my contribution, I will also draw on thinkers from the phenomenological tradition ranging from Bernhard Waldenfels, who has written of the merits of what he calls the ‘Stachel’ of the other, to Emmanuel Levinas’s ethics of alterity.

Topic Modeling as a Tool to Gauge Political Sentiments from Twitter Feeds

As ubiquitous as it is, the Internet has spawned a slew of products that have forever changed the way one thinks of society and politics. This article proposes a model to predict chances of a political party winning based on data collected from Twitter microblogging website, because it is the most popular microblogging platform in the world. Using unsupervised topic modeling and the NRC Emotion Lexicon, the authors demonstrate how it is possible to predict results by analyzing eight types of emotions expressed by users on Twitter. To prove the results based on empirical analysis, the authors examine the Twitter messages posted during 14th Gujarat Legislative Assembly election, 2017. Implementing two unsupervised clustering methods of K-means and Latent Dirichlet Allocation, this research shows how the proposed model is able to examine and summarize observations based on underlying semantic structures of messages posted on Twitter. These two well-known unsupervised clustering methods provide a firm base for the proposed model to enable streamlining of decision-making processes objectively.

Adoption of Multilingual State Emergency Management Websites: Responsiveness to the Risk Communication Needs of a Multilingual Society

ABSTRACT This article draws on the risk communication and responsiveness literature for theoretical context to investigate the adoption of multilingual websites at state emergency management agencies. It analyzes the 50 state websites on their multilingual presence of emergency-related information available to the public. It uses a binary logistic regression to model the determinants of their multilingual e-government usage for risk communication. The study reveals that state emergency management agencies adopt multilingual websites (1) to be responsive to the needs of populations who may not speak English, (2) to reduce state and immigrant vulnerability to disasters through effective risk communication, and finally (3) when better economic conditions prevail in their states. The study also supports the idea that public administrators are not driven by prevailing political and ideological sentiments in the states when making policies to communicate risk. By adopting multilingual websites, states are demonstrating that a multilingual society constitutes an important collective voice.

RELIGIOUS AND POLITICAL PUBLIC SENTIMENT TOWARDS POLITICAL CAMPAIGN IN SOCIAL MEDIA: INDONESIA AND MALAYSIA CASES

Purpose of the study: This paper depicts the use of social media for political campaign in Indonesia and Malaysia whilst especially aiming at investigating religious and political sentiment of Indonesian (young) voters (reflected in their Twitter accounts, especially the tweets and memes) that supported Joko Widodo-Jusuf Kalla (hereafter Jokowi’s camp) and Prabowo Subianto-Hatta Rajasa camps (hereafter Prabowo’s camp) in the 2014 Presidential Election Indonesia.
 Methodology: This qualitative study is a discourse analysis that deploys the Hallidayean transitivity system, language evaluation theory as well as social semiotics. Using stratified purposeful sampling, the data (tweets and memes of two contest political camps – the Islamic(/st?) versus the Nationalist) were taken during the campaign days (4 June –5 July 2014).
 Main Findings: In the Indonesian case, the (c)overt black campaign of both camps operates in the framework of the contestation as well as the synthesis of the nationalist/Islamic(/st?) strands. They are deployed to be rhymed in the brand resonance the both camps’ campaign team forged. As for Malaysian, the use of social media platforms by its young electorates did not guarantee the popularity gained by the (legislative) candidates, as they overlooked the people’s collective memories of the 1998 Reform Movement that resonated with Malaysian identity.
 Implicationof this study: As a preliminary part of multiyear research funded by Indonesia’s Ministry of Research, Technology and Higher Education, the findings become the textual foundation in producing the recommendation for public policy on the political campaign in social media (in this case the Twitter). Compared to other social media platforms, Twitter was chosen as it provides limited numbers of characters for its users (especially the two main camps – Jokowi’s versus Prabowo’s camps), not only to tweet but that more importantly also the tweets represent the perennial discursive contestation of the Islamic (-/st?) versus Nationalist strands to the current 2019 elections Indonesia.
 Novelty/Originality of this study: The (c)overt black campaign of both camps operates in the framework of the contestation as well as the synthesis of the nationalist/Islamic(/st?) strands. They are deployed to be rhymed in the brand resonance the campaign team forged. A similar contesting strategy is deployed, such as countering similar religious and political issues that represent the supporters/volunteers(read also: public) sentiment in the cyberwar (in the form of utterance and visual war).

Political Sentiment and Syndicated Loan Borrowing Costs of Multinational Enterprises

International business literature widely recognizes that political forces play a crucial role in modern corporations. Yet, rare are the studies of how foreign operations mitigate the detrimental effect that firm-level political exposure has on the cost of lending. We study such channels in a sample of U.S. corporations with foreign subsidiaries in 69 countries. We proxy firm-level political exposure via political sentiment. We show that firms with lower political sentiment (i.e., higher political exposure) have a higher cost of lending. We document that multinational enterprises with a presence in many countries, and those having an extended network of foreign subsidiaries can lower the harmful effects of increased political uncertainty. This outcome also holds in the presence of foreign economies of scale, and when multinational corporations have foreign subsidiaries in countries with higher political polarization.

АНТИРАДЯНСЬКІ НАСТРОЇ МІСЬКОГО НАСЕЛЕННЯ ІЗМАЇЛЬСЬКОЇ ОБЛАСТІ УРСР У ПОВОЄННИЙ ПЕРІОД (1944–1954)

The work researches essential reasons for spreading anti-Soviet public sentiments among local inhabitants of Izmail Region, Ukrainian Soviet Socialist Republic in the post-war period, describes their specific features and forms of counteraction to Soviet reformation and Communist totalitarian regime. Source basis of the said research is represented by documents of the Central State Archives of Public Organizations of Ukraine and the State Archives of Odessa Region. General reports and statements of activities from Regional Attorney Office Fund, SAOR, as well, as statistics data, reports and accounts in cases of special jurisdiction of Regional Attorney Office. Furthermore, reports of Soviet Administration and Communist Party figures, special notifications referring to armed force censorship, reports by PCHA about local inhabitants' sentiments, documentation describing the course of operation of kulaks' deportation. Documentation of Organization and Instruction Section of Communist Party of Ukraine Central Committee, CSAPO fund was also used: reports about the activities of military section of Communist Party Regional Committee, internal memoranda, statements of completed work. Special attention has been paid to review of display of discontent in matters of religious policy, particularly, activities of underground religious associations. Author also describes resistance of the local population to mobilization to Soviet industrial enterprises, specified number of deserters from enterprises of military industry. Author also revealed and described social and political sentiments in the first months of Soviet power implementation and changes in such sentiments which occurred due to drop in social standards and housing problems. It was discovered also that illegal actions of local Communist Party and Soviet Administration and individual public figures formed additional factors, which contributed to popular discontent.