Comparing Twitter and YouTube networks in information diffusion: The case of the “Occupy Wall Street” movement

Park, Se Jin; Lim, Yon Soo; Park, Han Woo

doi:10.1016/j.techfore.2015.02.003

Cited by 78 publications

(42 citation statements)

References 25 publications

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“…The importance of gaining product information from other social media participants is gaining as many social media users have increased their fame and influence by sharing common ideas and cultural values through their interactions (S. J. Park, Limb, & Park, 2015). For example consumers evaluating a new cardio exercise machine are likely to seek out and read product evaluations from 'the elliptical lady.'…”

Section: Social Media Communication (Content Positive Valence and Nementioning

confidence: 99%

The impact of positive valence and negative valence on social commerce purchase intention

Hajli

2019

ITP

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Purpose New research emphasizes the importance of social communications in e-commerce purchase decision-making processes but there are many technical and social challenges such as multi-faceted trust concerns. How consumers view and value referent’s online testimonials, ratings, rants and raves, and product usage experiences remain an important factor that needs to be better understood. Social commerce as a relatively new stream in e-commerce yet is growing fast and gaining the attention of scholars and practitioners, especially due to recent revenue developments. Consistent with e-commerce websites that do not enable consumer feedback, trust is a challenging matter for consumers to consider when they visit social commerce websites. Researching trust models and influences is increasingly important especially with the proliferation of online word of mouth (WOM) strongly effecting many consumers at many different phases of social commerce purchase decision making and transacting. The paper aims to discuss this issue. Design/methodology/approach This study examines the effects and importance of institution-based trust and WOM within a model of consumer behaviour on social commerce websites. This research examines how trust and consumer feedback may affect consumers’ purchase intentions. This study collects data from the little-understood market of urban Iran and develops a research model to examine consumers’ purchase intentions on social commerce websites. A robust data set from urban Iran (n=512) is analyzed using partial least squares regression to analyze the proposed model. Findings The results of the analysis show that institution-based trust influences social media communication, leading to elevated purchase intention on social commerce websites. This research adds to the prior literature that espouses on the importance of consumers developing strong beliefs of vendor trust in social commerce platforms. Originality/value Explaining how consumer purchase decision making is effected by using institution-based trust and electronic WOM in a little understood Middle Eastern context an important contribution of this research. Suggestions on practical and theoretical developments of this research in the sharing commerce research stream conclude this paper.

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Section: Social Media Communication (Content Positive Valence and Nementioning

confidence: 99%

The impact of positive valence and negative valence on social commerce purchase intention

Hajli

2019

ITP

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“…Co-occurrence is also widely observed in webometric data. For example, prior studies examine semantic networks based on co-occurrence of words in various social media posts (Kim, Heo, Choi, & Park, 2014;Shapiro & Park, 2015;Xu et al, 2015Xu et al, , 2016Park, Lim, & Park, 2015). Co-occurrence of words can reveal thematic/topic similarity and variation in online public discussions of issues (Heo, Park, Kim, & Park, 2016), or the media's framing of international events (Jiang, Barnett, & Taylor, 2016).…”

Section: Applying Network Analysis To International Relationsmentioning

confidence: 99%

Measuring international relations in social media conversations

Barnett

Chu

et al. 2017

Government Information Quarterly

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a b s t r a c t a r t i c l e i n f oThis paper examines international relations as perceived by the public in their social media conversations. It examines over 1.8 billion Facebook postings in English and 51 million Chinese posts on Weibo, to reveal the relations among nations as expressed in social media conversations. It argues that social media represent a transnational electronic public sphere, in which public discussions reveal characteristics of international relations as perceived by a foreign public. The findings show that the international relations in social media postings match the core-peripheral structure proposed in the World Systems Theory. Additionally, the relations are associated with the amount of news coverage and public attention a country receives. Overall, the study demonstrates the value of webometric data in revealing how international relations are perceived by average citizens.

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“…In particular, social network analysis is used as one of the big data analysis techniques, which is easy to understand the semantics of the network by grasping the frequency of appearance of key words. The most commonly used indicator among social network analysis indicators is centrality, which allows one actor to identify which nodes play a major role in the entire network (Park et al, 2015). Indicators for centrality analysis include degree centrality and closeness centrality based on the connectivity between objects, betweenness centrality based on intermediary between entities, and eigenvector centrality based on the weight of the relative connectivity of individuals (Scott, 2017;Wasserman & Frust, 1994).…”

Section: B Social Network Analysismentioning

confidence: 99%

“…It takes into account the centrality of directly connected entities as well as indirectly linked entities, so that words with overall influence in the network can be identified. Assuming that words with high centrality values affect other words (Park et al, 2015), a user with a high centrality can be regarded as the most influential core user. Words such as hypothetical (0.039), trading (0.037), technology (0.035), future (0.030), finance (0.030), and hacking (0.030) can be interpreted as having high effects.…”

Section: B Analysis Of Powerful Words In the Networkmentioning

confidence: 99%

Technology Predicting the Future using Data Mining Techniques

Moon*,

Kim*

2020

IJRTE

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The technologies of the future society can make a super connective society where everything is connected and organically interacted, and it promotes “Hyper-Connected”, “Hyper-Intelligent”, "Hyper-Real" as it is possible to become intellectual by techniques such as artificial intelligence and big data analysis. To find out the key triggers by extracting the technologies with these characteristics and identifying what factors and forms are used allows us to grasp changes in the industry due to the rapidly changing domestic environment and the influence of innovation technologies. According to the analysis, the key triggers of major technologies in information society are keywords such as security, technology, service, virtual, and finance which have a great chance to converge with other technologies. The implications of this study are as follows. First, key technologies of domestic information society were identified based on a huge amount of reliable news data. In addition, Network Analysis based on Data, which has increased the frequency of studies all over the field including computer science, sociology and business administration, is applied to predicting the future. Based on this, the methodology has been proposed that can be used to predict the pattern of technology development or notable technologies in the future. This study wasn’t conducted only on one detailed technology, but comprehensively on major technologies extracted in the era of 4th Industrial Revolution and presents Black Swan Prediction to enhance competitiveness of domestic industry in related technologies and create new added value.

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Comparing Twitter and YouTube networks in information diffusion: The case of the “Occupy Wall Street” movement

Cited by 78 publications

References 25 publications

The impact of positive valence and negative valence on social commerce purchase intention

The impact of positive valence and negative valence on social commerce purchase intention

Measuring international relations in social media conversations

Technology Predicting the Future using Data Mining Techniques

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