Measuring Political News Information Exposure using Text Analysis & Network Analysis

2019 ◽  
2018 ◽  
Vol 11 (4) ◽  
pp. 433-446 ◽  
Author(s):  
Fallon R. Mitchell ◽  
Sara Santarossa ◽  
Sarah J. Woodruff

The present study aimed to explore the interactions and influences that occurred on Twitter after Joey Julius’s (NCAA athlete, Penn State Football) and Mike Marjama’s (MLB player, Seattle Mariners) eating-disorder (ED) diagnoses were revealed. Corresponding with the publicizing of each athlete’s ED, all publicly tagged Twitter media using @joey_julius, Joey Julius, @MMarjama, and Mike Marjama were collected using Netlytic software and analyzed. Text analysis revealed that the conversation was supportive and focused on feelings and size. Social network analysis, based on 5 network properties, showed that Joey Julius invoked a larger conversation but that both athletes’ conversations were single sided. Athlete advocacy on social media should be further explored, as it may contribute to changing societal opinion regarding social issues such as EDs.


2021 ◽  
Vol 6 (1) ◽  
pp. 107-120
Author(s):  
Nurul Hasfi ◽  
Wijayanto Wijayanto

Objectivity (unbiased) news is an essential journalism principle in covering political news, especially general elections. However, many studies found that violations against these principles were becoming a problem in many elections in different countries. In Indonesia, most research concerns this issue more focusing on the traditional media platform. This article has aimed to explore online media on how they covered the 2019 presidential election. This research combines quantitative and qualitative text analysis methods to investigate 320 online media articles produced by eight leading online media in Indonesia two weeks before the election. By employing the journalism principle of objectivity, the concept of framing and representation, this research found that online media in Indonesia practice biased journalism in reporting the 2019 presidential election. However, each online media has a typical media bias both quantitatively and qualitatively. This study identified two categories of journalism practice, namely partisan journalism that openly supported particular candidates and at the same time attacked the rival. Secondly, the online media category tried to be professional, but they applied journalism bias by construction framing strategy and representation for the candidate they supported. This research also highlights that the bias of online media journalism was facilitated by the general principle of digital journalism routine in Indonesia that mostly focuses on speed rather than on comprehensive information and also facilitated by the existence of the hyper-link feature that legitimizes the 'cover one side' in a single article.


2019 ◽  
Vol 7 (3) ◽  
pp. 32-41 ◽  
Author(s):  
Benjamin A. Lyons

Studies of selective exposure have focused on use of traditional media sources. However, discussion networks are an integral part of individuals’ information diets. This article extends the selective exposure literature by exploring the potential for networks to likewise be selectively accessed. A pre-registered experiment found that participants nominate denser, more ideologically coherent networks in response to congenial political news relative to uncongenial news, and express willingness to share it with more people. Analysis of open-ended data suggest shared political beliefs are more likely to motivate discussant selection in response to congenial, rather than uncongenial, news. Properties of networks generated in response to political and non-political news did not vary. These results provide nuance to our understanding of political information exposure.


2018 ◽  
Vol 17 (4) ◽  
pp. 25
Author(s):  
Katalin Fehér

Tanulmányunk célja globális látleletet adni az aktuális okos város trendtémákról és koncepciókról a legnépszerűbb nyilvános, kollaborációs dokumentációk alapján. A témát először a tudományos szakirodalom változó hangsúlyainak rövid összefoglalása vezeti fel. Ezt követően kormányzati, üzleti és egyetemi-kutatási együttműködések dokumentumai alapján egy szisztematikus összeállított korpusz bemutatására kerül sor. Az elemzési módszertan ismertetése után kvantitatív szövegelemzésre és szöveg alapú kapcsolatháló-elemzésre kerül sor az aktuális trendtémák kimutatásához. Végül a korpuszban legtöbbet hivatkozott koncepciók rövid ismertetése következik. A végeredmény egy olyan összegzés, mely ajánlásokat fogalmaz meg az okos város tervezéshez a tudományos szakirodalom, a legnépszerűbb és legkeresettebb, széles nyilvánosságnak szóló, összefoglaló dokumentációkban megfogalmazott aktuális trend témák, illetve a kutatási korpuszon legtöbbet hivatkozott városkoncepciók alapján. --- Smart city trends and concepts according to the most popular collaborative documentation The purpose of our paper is to provide a global perspective of the current smart city trend topics and concepts of most popular and collaborative public documents. The field is first presented by a brief summary of its changing emphasis on scientific literature. Therefore, a systematic filtered corpus will be presented based on documents of governmental, business and university research co-operation. After describing the methodological concerns, a quantitative text analysis and text-based network analysis are formulated for detection of current trend topics. Last but not least, the most referred concepts of the corpus are briefly expounded. The outcome is a summary of recommendations for smart city planning applying the scientific literature, the most popular and public documentation of current trend topics, and the most referred city concepts according to the research corpus.


Information ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 19
Author(s):  
Yelim Mo ◽  
Euntaek Seon ◽  
Goun Park ◽  
Haklae Kim

Curriculums play a key role in implementing the educational goals and directions of a university. Universities regularly update their curriculums to actively respond to internal and external environmental changes. Korean universities face challenges, including a steady decline in enrollment and demand-oriented convergence education. Because of the nature of convergence science, library and information science should respond more actively to new challenges. This study analyzes the current status of library and information science courses according to subjects and universities. Data was collected from the websites of each university, and various methods such as text analysis, frequency analysis, and network analysis were applied to investigate current status of LIS in Korea.


2021 ◽  
Vol 13 (8) ◽  
pp. 4123
Author(s):  
Hyundong Nam ◽  
Taewoo Nam

This study aims to understand the global environment of COVID-19 management and guide future policy directions after the pandemic crisis. To this end, we analyzed a series of the World Economic Forum’s COVID-19 response reports through text mining and network analysis. These reports, written by experts in diverse fields, discuss multidimensional changes in socioeconomic situations, various problems created by those changes, and strategies to respond to national crises. Based on 3897 refined words drawn from a morphological analysis of 26 reports (as of the end of 2020), this study analyzes the frequency of words, the relationships among words, the importance of specific documents, and the connection centrality through text mining. In addition, the network analysis helps develop strategies for a sustainable response to and the management of national crises through identifying clusters of words with similar structural equivalence.


1996 ◽  
Vol 35 (4) ◽  
pp. 657-665 ◽  
Author(s):  
Carl W. Roberts ◽  
Roel Popping

Recent approaches to the qualitative analysis of texts afford visual depictions of words as networks. Yet network characteristics can also be quantified, enabling one to draw probabilistic inferences about a population of texts from a sample of texts-encoded-as-networks. This article describes three types of ambiguity (and related methodological problems) that arise during three necessary steps in the quantification of texts as networks: idiomatic ambiguity (in the identification of themes [or nodes]); illocutionary ambiguity (in the identification of syntactic links [or arcs]); and relevance ambiguity (in the identification of network characteristics). As one moves from theme to syntax to network, not only does one add complexity to one's conclusions, but one also adds complexity to the encoding process as distinct types of linguistic ambiguity must be resolved. The added complexity of network encoding will be unnecessary for most research questions - questions that might better be addressed via thematic or semantic text analysis.


2020 ◽  
Vol 6 (1) ◽  
pp. 34
Author(s):  
Lady Joanne Tjahyana

Digital Movement of Opinion (DMO) using hashtag #TrueBeauty on Twitter was conducted by the fans of True Beauty as one of the most popular Webtoon’s comic. The fans gave their opinion about the perfect cast for the movie adaption of the comic. The objective of this research is to analyse the network that was formed by the DMO of #TrueBeauty. The method that had been used was social network analysis and the datasets mining was done using Netlytic. This research indicates that fans as the actors of the DMO were spreaded widely across the network and not centralized into certain dominant actors. The actors was divided into different clusters and every cluster has its own characteristics based on different locations and cultures. Therefore the role of influencers or dominant actors in every cluster is very important to deliver opinions with a style that suits every community. Moreover, text analysis found that film industry should pay attention to social media opinion, because many of the opinion were reflects the original desires of every fan without any intermediaton from any parties.


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