Topic Modelling Extraction of “Mann Ki Baat”

2021 ◽  
Vol 2 (1) ◽  
pp. 1-12
Author(s):  
Mounika Kandukuri ◽  
HaraGopal V.V.
Keyword(s):  
Public Relations ◽  
Data Analytics ◽  
Latent Dirichlet Allocation ◽  
Statistical Modelling ◽  
Analytical Framework ◽  
Conventional Technique ◽  
Topic Modelling ◽  
Textual Data ◽  
Public Relations Campaign ◽  
Radio Programme

The purpose of this study is to give an insight about Textual Data analytics and its application in the analysis of unique public relations campaign”Mann Ki Baat” that was initiated by incumbent Prime Minister of India,honourable “Mr.Narendra Modi” which was initially aired on All India Radio Programme on Vijaya Dashami on October 3rd , 2014 followed by second on November 2nd, 2014 of the same year till December 2019. In this paper, an analytical framework is designed using a powerful technique of textual data analytics “Topic Modelling based on LDA (Latent Dirichlet Allocation)” to accomplish the study. The proposed framework is applied to the corpus of 60 episodes(October 2014 to December 2019) of Mann ki Baat gathered from PMindia website and  was analyzed in greater detail. The terms used frequently and recurrence of the topics spoken in his popular monthly radio address  program were determined and analyzed from both in statistical and dynamic perspectives.In this context the present study is a first approach of application under the conventional technique “topic modelling” on Mann Ki Baat.Further, this is the principal endeavour to excerpt the themes discussed in radio programme using statistical modelling.

scholarly journals Topic Modelling on Pharmaceutical Incident Data

2021 ◽  
Vol 2 (3) ◽  
pp. 92-96
Author(s):  
Deepu Dileep ◽  
Soumya Rudraraju ◽  
V. V. HaraGopal
Keyword(s):  
Pharmaceutical Industry ◽  
Key Words ◽  
Latent Dirichlet Allocation ◽  
Topic Modelling ◽  
Probability Of Occurrence ◽  
Proposed Model ◽  
Textual Data ◽  
Incident Data ◽  
Dirichlet Allocation

Focus of the current study is to explore and analyse textual data in the form of incidents in pharmaceutical industry using topic modelling. Topic modelling applied in the current study is based on Latent Dirichlet Allocation. The proposed model is applied on a corpus containing 190 incidents to retrieve key words with highest probability of occurrence. It is used to form informative topics related to incidents.

Integrating Big Data Into Evaluation: R Code for Topic Identification and Modeling

2021 ◽  
pp. 109821402110316
Author(s):  
Dakota W. Cintron ◽  
Bianca Montrosse-Moorhead
Keyword(s):  
Big Data ◽  
Topic Modeling ◽  
Data Analytics ◽  
Latent Dirichlet Allocation ◽  
Big Data Analytics ◽  
Specific Topic ◽  
Topic Identification ◽  
Ethical Concerns ◽  
Textual Data ◽  
R Packages

Despite the rising popularity of big data, there is speculation that evaluators have been slow adopters of these new statistical approaches. Several possible reasons have been offered for why this is the case: ethical concerns, institutional capacity, and evaluator capacity and values. In this method note, we address one of these barriers and aim to build evaluator capacity to integrate big data analytics into their studies. We focus our efforts on a specific topic modeling technique referred to as latent Dirichlet allocation (LDA) because of the ubiquitousness of qualitative textual data in evaluation. Given current equity debates, both within evaluation and the communities in which we practice, we analyze 1,796 tweets that use the hashtag #equity with the R packages topicmodels and ldatuning to illustrate the use of LDA. Furthermore, a freely available workbook for implementing LDA topic modeling is provided as Supplemental Material Online.

Evolution of COVID-19 Tweets about Southeast Asian Countries: Topic Modelling and Sentiment Analyses (Preprint)

2021 ◽  
Author(s):  
Boonyanit Mathayomchan ◽  
Viriya Taecharungroj ◽  
Walanchalee Wattanacharoensil
Keyword(s):  
Public Health ◽  
Public Relations ◽  
Public Discourse ◽  
Latent Dirichlet Allocation ◽  
Global Scale ◽  
Topic Modelling ◽  
Brand Association ◽  
The Many ◽  
Internal And External Factors ◽  
Compare And Contrast

BACKGROUND Emergence and evolution of online discourse on Twitter concerning the COVID-19 pandemic are crucial for public health and public relation officials to understand the prevailing perception of the disease and its impact. Despite the global scale of this pandemic, comparison and contrast of topics, sentiment and emotions of tweets among countries are limited. Further, most previous studies covered a short timeframe due to the recency of the event and the large volume of tweets. OBJECTIVE The purposes of this research were to 1) identify the multiplicity of public discourse during the COVID-19 pandemic and how they evolved, (2) compare and contrast sentiment levels and (3) compare emotions about countries over time. METHODS The research scope covered ten countries in Southeast Asia (SEA). We analysed 115,553 tweets that mentioned these countries from 22 January 2020 to 31 July 2021 using a topic modelling algorithm (latent Dirichlet allocation — LDA), VADER and NRC sentiment analyses. RESULTS We identified the emergence and evolution of twelve topics that were further grouped into early, parallel and late discourse. Each country had distinct topics and trends depending on differing internal and external factors. Sentiment improved with positive tweets of hope and fell when negative narratives predominated as a result of new waves of COVID-19. Four emotions that are prevalent during the pandemic were trust, fear, anticipation and sadness CONCLUSIONS This research detected the many divergent phases and faces of the pandemic on Twitter, the intertwined discourse of a double disaster and the role played by an infodemic on place brand association. Our results will assist public health and public relations officials to better understand how public discourse emerged and evolved with the COVID-19 pandemic.

scholarly journals News media attention in Climate Action: latent topics and open access

2021 ◽  
Author(s):  
Tahereh Dehdarirad ◽  
Kalle Karlsson
Keyword(s):  
Sustainable Development ◽  
Regression Analysis ◽  
Open Access ◽  
News Media ◽  
Latent Dirichlet Allocation ◽  
Topic Modelling ◽  
Sustainable Development Goal ◽  
Data Set ◽  
Development Goal ◽  
Climate Action

AbstractIn this study we investigated whether open access could assist the broader dissemination of scientific research in Climate Action (Sustainable Development Goal 13) via news outlets. We did this by comparing (i) the share of open and non-open access documents in different Climate Action topics, and their news counts, and (ii) the mean of news counts for open access and non-open access documents. The data set of this study comprised 70,206 articles and reviews in Sustainable Development Goal 13, published during 2014–2018, retrieved from SciVal. The number of news mentions for each document was obtained from Altmetrics Details Page API using their DOIs, whereas the open access statuses were obtained using Unpaywall.org. The analysis in this paper was done using a combination of (Latent Dirichlet allocation) topic modelling, descriptive statistics, and regression analysis. The covariates included in the regression analysis were features related to authors, country, journal, institution, funding, readability, news source category and topic. Using topic modelling, we identified 10 topics, with topics 4 (meteorology) [21%], 5 (adaption, mitigation, and legislation) [18%] and 8 (ecosystems and biodiversity) [14%] accounting for 53% of the research in Sustainable Development Goal 13. Additionally, the results of regression analysis showed that while keeping all the variables constant in the model, open access papers in Climate Action had a news count advantage (8.8%) in comparison to non-open access papers. Our findings also showed that while a higher share of open access documents in topics such as topic 9 (Human vulnerability to risks) might not assist with its broader dissemination, in some others such as topic 5 (adaption, mitigation, and legislation), even a lower share of open access documents might accelerate its broad communication via news outlets.

Kerntechnik als Sicherheitsversprechen

2021 ◽  
Vol 29 (84) ◽  
pp. 99-112
Author(s):  
Sascha Brünig
Keyword(s):  
Public Relations ◽  
Nuclear Power ◽  
Nuclear Industry ◽  
Industrial Society ◽  
Electricity Production ◽  
Nuclear Technology ◽  
Reactor Accident ◽  
The West ◽  
The Face ◽  
Public Relations Campaign

Abstract In the mid-1970s, the dangers associated with nuclear power moved to the center of risk debates in Germany. Following the reactor accident at Three Mile Island (1979) and the Chernobyl disaster (1986), the West German nuclear industry’s business prospects severely deteriorated. How did the nuclear industry perceive and confront the challenge of nuclear skepticism? And how did this emerging challenge alter the perceived future of nuclear technology in the Federal Republic and beyond? The article argues that the nuclear industry did not passively accept the »depletion of utopian energies« (J. Habermas) to which the peaceful use of the atom was subjected. Instead, the industry worked to create new (utopian) prospects for nuclear power. The industry’s public relations campaign positioned nuclear power in two interrelated fields of insecurity: the decline of industrial society and environmental crises. Both threats, ran the argument put forth by nuclear proponents, could only be combatted by relying on nuclear power for electricity production. In this way, nuclear power was translated into a comprehensive promise of security that was intended to salvage the future of nuclear power as well as that of its investors in the face of growing anti-nuclear sentiment.

The Public Image of Eastern Orthodoxy

2020 ◽  
Author(s):  
Heather L. Bailey
Keyword(s):  
Public Relations ◽  
Public Image ◽  
Russian Orthodox ◽  
Crimean War ◽  
The West ◽  
Eastern Orthodoxy ◽  
Russian Orthodox Church ◽  
The Public ◽  
Vatican Council ◽  
Public Relations Campaign

Focusing on the period between the revolutions of 1848 to 1849 and the First Vatican Council (1869–1870), this book explores the circumstances under which westerners, concerned about the fate of the papacy, the Ottoman Empire, Poland, and Russian imperial power, began to conflate the Russian Orthodox Church with the state and to portray the Church as the political tool of despotic tsars. As the book demonstrates, in response to this reductionist view, Russian Orthodox publicists launched a public relations campaign in the West, especially in France, in the 1850s and 1860s. The linchpin of their campaign was the building of the impressive Saint Alexander Nevsky Church in Paris, consecrated in 1861. The book posits that, as the embodiment of the belief that Russia had a great historical purpose inextricably tied to Orthodoxy, the Paris church both reflected and contributed to the rise of religious nationalism in Russia that followed the Crimean War. At the same time, the confrontation with westerners' negative ideas about the Eastern Church fueled a reformist spirit in Russia while contributing to a better understanding of Eastern Orthodoxy in the West.

A Case Study of K-Water Public Relations Campaign in Korea

2014 ◽  
Vol 2 (1) ◽  
pp. 1-6
Author(s):  
Seung-jun Moon ◽  
Jong Dae Kim ◽  
Tae Woo Kim
Keyword(s):  
Public Relations ◽  
Public Relations Campaign

scholarly journals THE INFLUENCE OF PUBLIC RELATIONS CAMPAIGN #NOSTRAWMOVEMENT ON FAST FOOD RESTOURANT CONSUMER PARTICIPATION

2020 ◽  
Vol 8 (2) ◽  
pp. 116-124
Author(s):  
Siti Meisyaroh ◽  
Marcella Novena
Keyword(s):  
Public Relations ◽  
Fast Food ◽  
Quantitative Research ◽  
Consumer Participation ◽  
Test Reliability ◽  
Consumer Attitude ◽  
The Public ◽  
Normality Test ◽  
Fast Food Restaurants ◽  
Public Relations Campaign

News about environmental issues have led many companies and fast food restaurants like KFC started the Public Relations campaign movement with the theme #NOSTRAWMOVEMENT which was done simultaneously in all of their outlets in Indonesia. KFC Raden Inten becomes case in study. This study aims to determine the influence of the Public Relations campaign #NOSTRAWMOVEMENT will influence consumer participation in KFC Raden Inten. This research uses stimulus- respons (S-R) theory and participation concept which can be interpreted as taking part or taking a role in activities or activities. The author uses this theory because I want to know how much consumer participation is influenced by Public Relations campaign #NOSTRAWMOVEMENT of KFC. Participation is divided into two categories, direct participation and indirect participation. In this study, researchers used quantitative research with a descriptive and explanatory approach. Data collection techniques used in this study were documentation and questionnaire filling as part of the survey. Researchers used a survei method using a questionnaire. Data analysis techniques using validity test, reliability test, normality test, t test, F test and R2 test. Based on the data processing carried out, this study obtained the result that the relationship between the Public Relations campaign variables and consumer participation had a positive and significant influence.   Keywords: Public Relations Campaign, Consumer Participation, Consumer Attitude

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