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Many people do not possess the necessary savings to deal with unexpected financial events. People's biases play a significant role in their ability to forecast future financial shocks: they are typically overoptimistic, present-oriented, and generally underestimate future expenses. The purpose of this study is to investigate how varying risk information influences people's financial awareness, in order to reduce the chance of a financial downfall. Specifically, we contribute to the literature by exploring the concept of 'nudging' and its value for behavioural changes in personal financial management. While of great practical importance, the role of nudging in behavioural financial forecasting research is scarce. Additionally, the study steers away from the standard default choice architecture nudge, and adds originality by focusing on eliciting implementation intentions and pre-commitment strategies as types of nudges. Our experimental scenarios examined how people change their financial projections in response to nudges in the form of new information on relevant risks. Participants were asked to forecast future expenses and future savings. They then received information on potential events identified as high-risk, low-risk or no-risk. We investigated whether they adjusted their predictions in response to various risk scenarios or not and how such potential adjustments were affected by the information given. Our findings suggest that the provision of risk information alters financial forecasting behaviour. Notably, we found an adjustment effect even in the no-risk category, suggesting that governments and institutions concerned with financial behaviour can increase financial awareness merely by increasing salience about possible financial risks. Another practical implication relates to splitting savings into different categories, and by using different wordings: A financial advisory institution can help people in their financial behaviour by focusing on 'targets', and by encouraging (nudging) people to make ...

Many people do not possess the necessary savings to deal with unexpected financial events. People's biases play a significant role in their ability to forecast future financial shocks: they are typically overoptimistic, present-oriented, and generally underestimate future expenses. The purpose of this study is to investigate how varying risk information influences people's financial awareness, in order to reduce the chance of a financial downfall. Specifically, we contribute to the literature by exploring the concept of 'nudging' and its value for behavioural changes in personal financial management. While of great practical importance, the role of nudging in behavioural financial forecasting research is scarce. Additionally, the study steers away from the standard default choice architecture nudge, and adds originality by focusing on eliciting implementation intentions and precommitment strategies as types of nudges. Our experimental scenarios examined how people change their financial projections in response to nudges in the form of new information on relevant risks. Participants were asked to forecast future expenses and future savings. They then received information on potential events identified as high-risk, low-risk or no-risk. We investigated whether they adjusted their predictions in response to various risk scenarios or not and how such potential adjustments were affected by the information given. Our findings suggest that the provision of risk information alters financial forecasting behaviour. Notably, we found an adjustment effect even in the no-risk category, suggesting that governments and institutions concerned with financial behaviour can increase financial awareness merely by increasing salience about possible financial risks. Another practical implication relates to splitting savings into different categories, and by using different wordings: A financial advisory institution can help people in their financial behaviour by focusing on 'targets', and by encouraging (nudging) people to make breakdown forecasts rather than general ones.

Purpose Using data from Twitter, the purpose of this paper is to assess the coping behaviour and reactions of social media users in response to the initial days of the COVID-19-related lockdown in different parts of the world. Design/methodology/approach This study follows the quasi-inductive approach which allows the development of pre-categories from other theories before the sampling and coding processes begin, for use in those processes. Data was extracted using relevant keywords from Twitter, and a sample was drawn from the Twitter data set to ensure the data is more manageable from a qualitative research standpoint and that meaningful interpretations can be drawn from the data analysis results. The data analysis is discussed in two parts: extraction and classification of data from Twitter using automated sentiment analysis; and qualitative data analysis of a smaller Twitter data sample. Findings This study found that during the lockdown the majority of users on Twitter shared positive opinions towards the lockdown. The results also found that people are keeping themselves engaged and entertained. Governments around the world have also gained support from Twitter users. This is despite the hardships being faced by citizens. The authors also found a number of users expressing negative sentiments. The results also found that several users on Twitter were fence-sitters and their opinions and emotions could swing either way depending on how the pandemic progresses and what action is taken by governments around the world. Research limitations/implications The authors add to the body of literature that has examined Twitter discussions around H1N1 using in-depth qualitative methods and conspiracy theories around COVID-19. In the long run, the government can help citizens develop routines that help the community adapt to a new dangerous environment – this has very effectively been shown in the context of wildfires in the context of disaster management. In the context of this research, the dominance of the positive ...

Purpose: The use of Twitter by political parties and politicians has been well studied in developed countries. However, there is a lack of empirical work which has examined the use of Twitter in developing countries. The present study aims to explore the information sharing patterns of Pakistani politicians through Twitter accounts during the pre-election campaign of 2018. Design/Methods/Methodology: Data of three weeks of the official party accounts and the politicians running for prime minister was analysed. The mixed methods approach has been employed to analyze quantitative and qualitative data retrieved through Twitonomy. Findings: It was found that the most active Twitter account belonged to the winning party. The prominent Twitter account functions were call to vote, promotional Tweets, promises and tweeting about party developments. The present studyprovides evidence that there is a difference between the tweeting behaviour of established and emerging parties. The emerging party heavily posted about changing traditional norms/culture/practices. Practical Implications: The study contributed to existing knowledge and has practical implications for politicians, citizens and social media planners. Originality/Value: The present study was designed carefully and based on empirical research. The study is unique in its nature to fill the research and knowledge gap by adding variety of Twitter functions used by politicians.

Purpose – The use of social media has increased during the COVID-19 pandemic. Social media platforms provide opportunities to share news, ideas and personal stories. Twitter is used by citizens in Pakistan to respond and comment on emerging news stories and events. However, it is not known whether Twitter played a positive or negative role in spreading updates and preventive messages during the COVID-19 Pandemic. The purpose of this study is to analyse content from Twitter during the pandemic. Design/methodology/approach – NodeXL was used to retrieve data using the keyword وائرس کورونا (written in Urdu and which translates to Coronavirus). The first data set (Case Study 1) was based on 10,284 Twitter users from the end of March. The second data set (Case Study 2) was based on 10,644 Twitter users from the start of April. The theoretical lens of effective message framing was used to classify the most retweeted content on Twitter. Findings – Twitter was used for personal and professional projections and included certain tweets included political motives even during the unfolding health crisis. There appeared to be very few successful attempts to use Twitter as a tool for health awareness and risk communication. The empirical findings indicate that the most retweeted messages were gain-framed and can be classified as personal, informative and political in nature. Originality/value – The present study provides insights likely to be of interest to researchers, health organizations, citizens, government and politicians that are interested in making more effective use of social media for the purposes of health promotion. The authors also provides novel insights into the key topics of discussions, websites and hashtags used by Pakistani Twitter users during the COVID-19. ; Output Status: Forthcoming/Available Online

Background: High compliance in wearing a mask is a crucial factor for stopping the transmission of COVID-19. Since the beginning of the pandemic, social media has been a key communication channel for citizens. This study focused on analyzing content from Twitter related to masks during the COVID-19 pandemic. Methods: Twitter data were collected using the keyword "mask" from 27 June 2020 to 4 July 2020. The total number of tweets gathered were n = 452,430. A systematic random sample of 1% (n = 4525) of tweets was analyzed using social network analysis. NodeXL (Social Media Research Foundation, California, CA, USA) was used to identify users ranked influential by betweenness centrality and was used to identify key hashtags and content. Results: The overall shape of the network resembled a community network because there was a range of users conversing amongst each other in different clusters. It was found that a range of accounts were influential and/or mentioned within the network. These ranged from ordinary citizens, politicians, and popular culture figures. The most common theme and popular hashtags to emerge from the data encouraged the public to wear masks. Conclusion: Towards the end of June 2020, Twitter was utilized by the public to encourage others to wear masks and discussions around masks included a wide range of users.

Objectives. Examine the online interactions, social networks, and perspectives of nursing actors on COVID-19 from conversations on Twitter to understand how the profession responded to this global pandemic. Design. Mixed methods. Sample. 10,574 tweets by 2,790 individuals and organisations. Measurements. NodeXL software was used for social network analysis to produce a network visualisation. The betweenness centrality algorithm identified key users who were influential in COVID-19 related conversations on Twitter. Inductive content analysis enabled exploration of tweet content. A communicative figurations framework guided the study. Results. Nursing actors formed different social groupings, and communicated with one another across groups. Tweets covered four themes; 1. outbreak and clinical management of the infectious disease, 2. education and information sharing, 3. social, economic, and political context, and 4. working together and supporting each other. Conclusion. In addition to spreading knowledge, nurses tried to reach out through social media to political and healthcare leadership to advocate for improvements needed to address COVID-19. However, they primarily conversed within their own professional community. Action is needed to better understand how social media is and can be used by nurses for health communication, and to improve their preparedness to be influential on social media beyond the nursing community.