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Social media are increasingly used as a source of health information. Opinions expressed on social media, including Twitter, may contribute to opinion formation and impact positively or negatively the vaccination decision-making process. The paper creates networks of Greek users that talk about vaccination on Twitter, during the last quarter of 2021 and analyzes their structure and grouping. Furthermore, some content analysis is also produced by creating networks of words found within tweets. The main purpose is to locate and present the Greek public views on COVID-19 vaccination. Results show that the network of Greek users may be considered as fragmented but by all means not polarized between two different opinions. Anti-vaccination ideas were clearly present during the first period of our study but were rapidly diminished in the following months, maybe due to a large number of deaths and the advent of the Omicron strain. The persisting large percentage of the population refusing to vaccinate may be expressed in other social media platforms.

This study aims at introducing a social network analysiss based methodology able to predict the financial fraud of companies. For this purpose, data obtained from financial statements and auditors reports for all Greek companies listed on the Athens Exchange during the period 2008–2015 has been used. Nineteen cases of possible fraud were found. These cases comprise the primary research sample with falsified financial statements (FFS). Furthermore, a control sample (non-FFS) consisting of companies with no fraud possibilities was constructed respectively. Various comparisons and several tests were applied, in order to find a network textual analysis model that could serve as a predictor of ‘red flags’ in the auditing process of financial statements for fraud. The results of this study could be useful to the banking sector, to internal and external auditors, to the tax or other state authorities, and to potential investors or business consultants.

Increasing numbers of museums use Twitter to attract visitors, engage effectively with them and facilitate the construction and strengthening of communities, where visitors are creating their own a...

The 2022–2023 winter period is alleged to be one of the toughest since World War II with respect to energy, especially electricity, natural gas and oil. The paper investigates the public discussions on Twitter in five widely spoken European languages and English. Networks of users are formed in order to locate possible important nodes that control the distribution of information. The networks are rather sparse and do not belong to the general class of ‘small worlds’. The communities of users seem to gather around one user; however, users also interact with others within the groups. Regarding the users’ sentiments, the negatives are definitely higher than the positive ones. Sentiments appear to be stable in their scores during the examined period and for each language; fear and sadness are dominant among them. Energy prices are frequently discussed in all languages, along with major political events. Findings may help governments to better understand public views and develop an effective strategy to communicate with and protect EU citizens.

Pictures speak louder than words. In this fast-moving world where people hardly have time to read anything, photo-sharing sites become more and more popular. Instagram is being used by millions of people and has created a “sharing ecosystem” that also encourages curation, expression, and produces feedback. Museums are moving quickly to integrate Instagram into their marketing strategies, provide information, engage with audience and connect to other museums Instagram accounts. Taking into consideration that people may not see museum accounts in the same way that the other museum accounts do, the article first describes accounts' performance of the top, most visited museums worldwide and next investigates their interconnection. The analysis uses techniques from social network analysis, including visualization algorithms and calculations of well-established metrics. The research reveals the most important modes of the network by calculating the appropriate centrality metrics and shows that the network formed by the museum Instagram accounts is a scale–free small world network.

In this paper we deal with Twitter and the presence of the keyword “Macedonia” in tweets over a period of time. We searched for the same term in three different languages, i.e. “Μακeδονiα”, “Macedonia” and “Македонска - Македониjа”, since we are primarily interested in views from Greece and FYROM without excluding views from other regions. We use methods from Social Network Analysis (SNA) in order to create networks of users, calculate some main network metrics, measure user importance and investigate the presence of possible fragmentations—communities among them. We furthermore proceed to a form of content analysis, using pairs of words within tweets, in order to obtain main ideas, trends and public views that circulated over the network.

The COVID-19 disease emerged in late 2019 in China, is still rapidly spreading across the globe. Greece as many other countries enforced strict preventative policies. As a result, the daily life of people has changed and conversation turned online. The paper aims at investigating discussions around COVID-19 on Twitter in Greece. Twitter was selected as it played a significant role during the global health crisis. The presence of the keywords “Κορονοιος”, “κορονοιός”, “κορωνοιος”, “Κορωνοϊός”, “Κορωνοιος” in tweets over four periods of time were recorded. NodeXL Pro was used to identify word pairs, create semantic networks and analyze them. Main topics of conversation were extracted. ‘New cases’ are heavily discussed all of the times showing anxiety about community transmission of the virus. A shift on different views was also recorded. Before the lockdown people showed their concerns about stocking up foods and other essentials, followed by positive hashtags in the fight to save lives and encouraging each other and finally the debate over the deaths. The paper may help policy makers regarding societal issues during the pandemic.

In this paper, we examine a set of Greek Listed Companies with respect to the interconnections between their Boards of Directors (BoD’s). Our main objective is to examine if and to what extent these Directors are interlocked, and if this possible interlocking may affect the course of economic or financial decisions through the information content of announced earnings, including implications on the current financial crisis in Greece. For this purpose, we use two different modes of research methodology, namely social network analysis and OLS methodology (panel analysis). The results of this study indicate the existence of a highly connected and interdependent network between companies and the people constitute the BoD’s. Also, the results show that in their entirety the companies are related and there is a high degree of interaction. These results lead to interesting theoretical and policy implications: could such a high interconnection lead to an extreme risk of total failure of the system in periods of hard times? To what extent should the state through its regulatory instruments (laws, market observers) try to affect the actual forming of Listed Companies BoD’s? Has this interlocking played its role in the Greek Economic Crisis, etc.?

In this paper, we seek to analyze pre-electoral political language in Greece with the use of Social Network Analysis. For this analysis, we collected data from the pre-elections speeches of five political leaders from the 20th of September 2015 Greek general elections. We proceed to form, analyze and compare networks of words with an emphasis on financial vocabulary. Findings can provide interesting insights into how political leaders structure their speeches, evaluate important issues and use economic terms and political rhetoric, while different structural patterns can reveal the differences between political parties. Finally, we check whether the overall networks follow the general rules of real-life networks by belonging to the small-world or scale-free categories.

Instagram, the photo and video sharing social network platform, has enjoyed exponential growth since its launch. As Instagram’s popularity is growing fast, museums are moving quickly to integrate it into their marketing strategies, provide information about exhibitions and objects, engage with audience and connect to other museums Instagram accounts. This paper aims at investing the interconnections among the Instagram accounts of the most visited museums worldwide. The analysis uses techniques from Social Network Analysis, including visualization algorithms and calculations of well-established metrics. The research shows that the network formed by the museum Instagram accounts is a scale-free small world network and reveals the most important nodes of the network. Depending or their marketing policies, other museums may follow the most important in the network, be aware of the information that flows in the network and also to be motivated and inspired by them.

Nowadays, museums, galleries and other cultural institutions use social media to reach millions of people, to build communities of interest, to perform marketing, engagement-focused and educational activities. Use of mobile devices in India is widespread, in contrast to Internet use which is low and it is, therefore, interesting to study the adoption and use of mobile applications like Instagram. The paper aims at investigating the use of Instagram by cultural institutions in India and takes into consideration four main performance indexes namely, the total number of followers, total number of accounts following, total number of posts and number of likes attracted by the last ten posts of the accounts in order to construct a weighed performance index. The proposed index shows that some of the Instagram accounts attempt to exploit the possibilities offered by Instagram to connect and effectively engage with their fans and boost their presence on the platform. Cultural institutions are important heritage destinations and generators of income. The creation of Instagram content that engages fans and followers and hopefully turn a proportion of followers to visitors may have positive impact for the institute and largely for the country.

Twitter offers tremendous opportunities for people to engage in discussion regarding the Oscars awards through information sharing, expressing opinions, disappointment or enthusiasm on movies, casts, and productions. Despite the huge number of tweets generated and the notable excitement about the Oscars, there is a void in the literature about the dynamic interconnections of users interacting in Twitter. In this paper, we use social network analytic techniques to record and create networks of users discussing and interacting in Twitter around the search term 'Oscars'. We subsequently present and study the users' networks gaining insights regarding their clusterability in communities and some of their discussion topics. We also study the macroscopic structure of the users' network and prove that they belong to a class of networks bearing the scale-free topology. Finally, we create new networks based on the actual content of the tweets, based on word adjacencies and we proceed with a similar investigation on these semantic networks.

In this paper we provide some insights in Homer's Iliad from the perspective of social network analysis. We use the original text and other public available data to create a social network (i.e. a graph) that comprises of all actors in the Iliad together with their interactions. We present some visualizations of these data and discuss concepts like connectivity, connected components and groupings. Furthermore, we calculate some well-established metrics, coming from social network analysis in this social network and discuss the numerical results. These results indicate that the Iliadic network is a small-world network, rather dissasortative and relatively easy to disconnect.

Technology ranks second among the top topics on blogging. However, little research effort has been devoted to investigating “tech” blogs while it is interesting to provide insights on their network, as they may have strong influence in the way that readers act and make decisions. In this vein, the paper records Greek “tech” blogs and their incoming links reported through their blogrolls. A directed network was created where blogs are noted as nodes and linked as directed arrows—arcs. The resulting network is analyzed using centrality and topological measurements and results are discussed in the social network analysis context. The network is a small world, with sparse density for a real-life social network and is low in-degree that shows off a kind of immaturity. Bloggers prefer to link to nodes with smaller degrees perhaps due to the fact that they are afraid of the growing competition thus they have reservations.

One of the obstacles women entrepreneurs face is their access to financing. As in the rest of the developed world, in the EU and Greece special financial tools were created, aiming at specific groups, in our case, women. This paper attempts to review relevant literature, to highlight the need for incentives to SMEs and in particular to women entrepreneurs, to list the financial instruments in the EU and Greece, which generally relate to SMEs, especially in women who own or will create a business. The specific financial tools to strengthen women's entrepreneurship in Greece, despite the steps taken in recent years, are still limited. Those tools are more or less the same for women as for all entrepreneurs.