A review of social media posts from UniCredit bank in Europe

Botchway, Raphael Kwaku; Jibril, Abdul Bashiru; Kwarteng, Michael Adu; Chovancová, Miloslava; Oplatková, Zuzana Komínková

doi:10.1145/3361785.3361814

Cited by 19 publications

(13 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Scores of -0.05 and under were negative, scores of +0.05 and above were positive, and scores in between were neutral. These thresholds are conventional for studies using VADER [19,20], and classification by human raters was found to be well-matched to VADER results when using these scoring thresholds [21].…”

Section: Sentiment Analysismentioning

confidence: 86%

Changes in Public Response Associated With Various COVID-19 Restrictions in Ontario, Canada: Observational Infoveillance Study Using Social Media Time Series Data

Chum¹,

Nielsen²,

Bellows³

et al. 2021

J Med Internet Res

View full text Add to dashboard Cite

Background News media coverage of antimask protests, COVID-19 conspiracies, and pandemic politicization has overemphasized extreme views but has done little to represent views of the general public. Investigating the public’s response to various pandemic restrictions can provide a more balanced assessment of current views, allowing policy makers to craft better public health messages in anticipation of poor reactions to controversial restrictions. Objective Using data from social media, this infoveillance study aims to understand the changes in public opinion associated with the implementation of COVID-19 restrictions (eg, business and school closures, regional lockdown differences, and additional public health restrictions, such as social distancing and masking). Methods COVID-19–related tweets in Ontario (n=1,150,362) were collected based on keywords between March 12 and October 31, 2020. Sentiment scores were calculated using the VADER (Valence Aware Dictionary and Sentiment Reasoner) algorithm for each tweet to represent its negative to positive emotion. Public health restrictions were identified using government and news media websites. Dynamic regression models with autoregressive integrated moving average errors were used to examine the association between public health restrictions and changes in public opinion over time (ie, collective attention, aggregate positive sentiment, and level of disagreement), controlling for the effects of confounders (ie, daily COVID-19 case counts, holidays, and COVID-19–related official updates). Results In addition to expected direct effects (eg, business closures led to decreased positive sentiment and increased disagreements), the impact of restrictions on public opinion was contextually driven. For example, the negative sentiment associated with business closures was reduced with higher COVID-19 case counts. While school closures and other restrictions (eg, masking, social distancing, and travel restrictions) generated increased collective attention, they did not have an effect on aggregate sentiment or the level of disagreement (ie, sentiment polarization). Partial (ie, region-targeted) lockdowns were associated with better public response (ie, higher number of tweets with net positive sentiment and lower levels of disagreement) compared to province-wide lockdowns. Conclusions Our study demonstrates the feasibility of a rapid and flexible method of evaluating the public response to pandemic restrictions using near real-time social media data. This information can help public health practitioners and policy makers anticipate public response to future pandemic restrictions and ensure adequate resources are dedicated to addressing increases in negative sentiment and levels of disagreement in the face of scientifically informed, but controversial, restrictions.

show abstract

Section: Sentiment Analysismentioning

confidence: 86%

Changes in Public Response Associated With Various COVID-19 Restrictions in Ontario, Canada: Observational Infoveillance Study Using Social Media Time Series Data

Chum¹,

Nielsen²,

Bellows³

et al. 2021

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…The effectiveness of social media has positively impacted the organizational and financial performance of Small and Medium Enterprises (Botchway et al, 2019;Seiler et al, 2020;Apenteng et al, 2020). Similarly, Gligor & Bozkurt, 2020;Odupitan, 2017;Nasir,2015 indicate that financial ailments of Small and Medium Enterprises are solved through social 31:MMCKS media usage.…”

Section: Financial Performancementioning

confidence: 99%

Antecedents of Sustainable SMEs in the Social Media Space: A Partial Least Square-Structural Equation Modeling (PLS-SEM) Approach

Amoah

Belás

Khan

et al. 2021

Management &Amp; Marketing. Challenges for the Knowledge Society

View full text Add to dashboard Cite

Social media has become explosive, permeating every sphere of the socio-cultural lives of individuals and businesses, and causing nations to technologically evolve. The dramatic growth in the adoption and use of social media has become beneficial to Small and Medium Enterprises (SMEs), significantly contributing to resolving a nagging challenge of effectively advertising their goods and services. Consequently, SMEs can achieve business growth and sustainability through increased adoption and harnessing the opportunities provided through the use of social media. The COVID-19 pandemic has provided an impetus for both consumers and SME businesses to leverage interaction through social media, which may lead to business growth. This research thus sets out to identify how social media contributes to the growth of SMEs within a developing country context. To accomplish this objective, primary data was collected from SMEs in the hospitality industry across the sixteen administrative regions of Ghana using survey and simple random sampling techniques. Questionnaires were distributed to the managerial staff of each randomly selected survey participant. Out of the 900 questionnaires distributed, 718 were filled correctly for the data analysis. The researchers quantitatively analyzed the responses using Partial Least Square-Structural Equation Modeling(PLSSEM) statistical software ADANCO 2.0 version. The results indicated that Small and Medium Enterprises are capable of using social media for customer attraction, business marketing strategy, communication channel and increased financial performance.

show abstract

“…From these, it is evident that social media data are used for to examine emerging technologies, product competitiveness or life cycle analysis and overall opinion gathering. As the increasing amount of social media data provides opportunities for building decision support systems regarding product or service improvement, some of these studies focus on processing the social media content for product-related feedback analysis (Botchway et al, 2019;Hasson et al, 2019;Jiang et al, 2011;Mirtalaie et al, 2017;Saura & Bennett, 2019).…”

Section: Related Workmentioning

confidence: 99%

Social media-based opinion retrieval for product analysis using multi-task deep neural networks

Gözüaçık

Şakar

Ozcan³

2021

Expert Systems with Applications

View full text Add to dashboard Cite

A review of social media posts from UniCredit bank in Europe

Cited by 19 publications

References 30 publications

Changes in Public Response Associated With Various COVID-19 Restrictions in Ontario, Canada: Observational Infoveillance Study Using Social Media Time Series Data

Changes in Public Response Associated With Various COVID-19 Restrictions in Ontario, Canada: Observational Infoveillance Study Using Social Media Time Series Data

Antecedents of Sustainable SMEs in the Social Media Space: A Partial Least Square-Structural Equation Modeling (PLS-SEM) Approach

Social media-based opinion retrieval for product analysis using multi-task deep neural networks

Contact Info

Product

Resources

About