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Article
Publication date: 14 March 2016

Umesh Rao Hodeghatta and Sangeeta Sahney

This paper aims to research as to how Twitter is influential as an electronic word-of-mouth (e-WOM) communication tool and thereby affecting movie market. In present days, social

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Abstract

Purpose

This paper aims to research as to how Twitter is influential as an electronic word-of-mouth (e-WOM) communication tool and thereby affecting movie market. In present days, social media is playing an important role in connecting people around the globe. The technology has provided a platform in the social media space for people to share their experiences through text, photos and videos. Twitter is one such online social networking media that enables its users to send and read text-based messages of up to 140 characters, known as “tweets”. Twitter has nearly 200 million users and billions of such tweets are generated by users every other day. Social media micro-blogging broadcasting networks such as Twitter are transforming the way e-WOM is disseminated and consumed in the digital world. Twitter social behaviour for the Hollywood movies has been assessed across seven countries to validate the two basic blocks of the honeycomb model – sharing and conversation. Twitter behaviour was studied for 27 movies in 22 different cities of seven countries and for six genres with a total tweets of 9.28 million. The difference of Twitter social media behaviour was compared across countries, and “sharing” and “conversation” as two building blocks of the honeycomb model were studied. t-Test results revealed that the behaviour is different across countries and across genres.

Design/methodology/approach

The objective of the paper is to analyse Twitter messages on an entertainment product (movies) across different regions of the world. Hollywood movies are released across different parts of the world, and Twitter users are also in different parts of the world. The objective is to hence validate “conversation” and “sharing” building blocks of the honeycomb model. The research is confined to analysing Twitter data related to a few Hollywood movies. The tweets were collected across nine different cities spanning four different countries where English language is prominent. To understand the Twitter social media behaviour, a crawler application using Python and Java was developed to collect tweets of Hollywood movies from the Twitter database. The application has incorporated Twitter application programming interfaces (APIs) to access the Twitter database to extract tweets according to movies search queries across different parts of the world. The searching, collecting and analysing of the tweets is a rather challenging task because of various reasons. The tweets are stored in a Twitter corpus and can be accessed by the public using APIs. To understand whether tweets vary from one country to another, the analysis of variance test was conducted. To assess whether Twitter behaviour is different, and to compare the behaviour across countries, t-tests were conducted taking two countries at a time. The comparisons were made across all the six genres. In this way, an attempt was made to obtain a microscopic view of the Twitter behaviour for each of the seven countries and the six genres.

Findings

The findings show that the people use social media across the world. Nearly 9.28 million tweets were from seven countries, namely, USA, UK, Canada, South Africa, Australia, India and New Zealand for 27 Hollywood movies. This is indicative of the fact that today, people are exchanging information across different countries, that people are conversing about a product on social media and people are sharing information about a product on social media and, thus, proving the hypothesis. Further, the results indicate that the users in USA, Canada and UK, tweet more than the other countries, USA and UK being the highest in tweets followed by the Canada. On the other hand, the number of tweets in Australia, India and South Africa are low with New Zealand being the lowest of all the countries. This indicates that different countries’ users have different social media behaviour. Some countries use social media to communicate about their experience more than in some other country. However, consumers from all over the world are using Twitter to express their views openly and freely.

Originality/value

This research is useful to scholars and enterprises to understand opinions on Twitter social media and predict their impact. The study can be extended to any products which can lead to better customer relationship management. Companies can use the Internet and social media to promote and get feedback on their products and services across different parts of the world. Governments can inform the public about their new policies, benefits of governmental programmes to people and ways to improve the Internet reach to more people and also for creating awareness about health, hygiene, natural calamities and safety.

Details

Journal of Systems and Information Technology, vol. 18 no. 1
Type: Research Article
ISSN: 1328-7265

Keywords

Article
Publication date: 15 October 2018

Xieling Chen, Shan Wang, Yong Tang and Tianyong Hao

The purpose of this paper is to explore the research status and development trend of the field of event detection in social media (ED in SM) through a bibliometric analysis of…

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Abstract

Purpose

The purpose of this paper is to explore the research status and development trend of the field of event detection in social media (ED in SM) through a bibliometric analysis of academic publications.

Design/methodology/approach

First, publication distributions are analyzed including the trends of publications and citations, subject distribution, predominant journals, affiliations, authors, etc. Second, an indicator of collaboration degree is used to measure scientific connective relations from different perspectives. A network analysis method is then applied to reveal scientific collaboration relations. Furthermore, based on keyword co-occurrence analysis, major research themes and their evolutions throughout time span are discovered. Finally, a network analysis method is applied to visualize the analysis results.

Findings

The area of ED in SM has received increasing attention and interest in academia with Computer Science and Engineering as two major research subjects. The USA and China contribute the most to the area development. Affiliations and authors tend to collaborate more with those within the same country. Among the 14 identified research themes, newly emerged themes such as Pharmacovigilance event detection are discovered.

Originality/value

This study is the first to comprehensively illustrate the research status of ED in SM by conducting a bibliometric analysis. Up-to-date findings are reported, which can help relevant researchers understand the research trend, seek scientific collaborators and optimize research topic choices.

Details

Online Information Review, vol. 43 no. 1
Type: Research Article
ISSN: 1468-4527

Keywords

Article
Publication date: 6 August 2019

Claire Monique Segijn, Ewa Maslowska, Theo Araujo and Vijay Viswanathan

The purpose of this paper is to explore the interrelationship between television (TV) consumption (viewing ratings), engagement behaviors of different actors on Twitter (TV…

Abstract

Purpose

The purpose of this paper is to explore the interrelationship between television (TV) consumption (viewing ratings), engagement behaviors of different actors on Twitter (TV programs, media, celebrities and viewers) and the content of engagement behaviors (affective, program-related and social content).

Design/methodology/approach

TV ratings and Twitter data were obtained. The content of tweets was analyzed by means of a sentiment analysis. A vector auto regression model was used to understand the interrelationship between tweets of different actors and TV consumption.

Findings

First, the results showed a negative interrelationship between TV viewing and viewers’ tweeting behavior. Second, tweets by celebrities and media exhibited similar patterns and were both affected mostly by the number of tweets by viewers. Finally, the content of tweets matters. Affective tweets positively relate to TV viewing, and program-related and social content positively relates to the number of tweets by viewers.

Research limitations/implications

The findings help us understand the online engagement ecosystem and provide insights into drivers of TV consumption and online engagement of different actors.

Practical implications

The results indicate that content producers may want to focus on stimulating affective conversations on Twitter to trigger more online and offline engagement. The results also call for rethinking the meaning of TV metrics.

Originality/value

While some studies have explored viewer interactions on Twitter, only a few studies have looked at the effects of such interactions on variables outside of social media, such as TV consumption. Moreover, the authors study the interrelations between Twitter interactions with TV consumption, which allows us to examine the effect of online engagement on offline behaviors and vice versa. Finally, the authors take different actors into account when studying real-life online engagement.

Details

Internet Research, vol. 30 no. 2
Type: Research Article
ISSN: 1066-2243

Keywords

Article
Publication date: 8 July 2014

Ilaria Dalla Pozza

This paper aims to investigate customers’ motivations and the decision-making process when choosing a channel in a “social” multichannel environment that includes social media

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Abstract

Purpose

This paper aims to investigate customers’ motivations and the decision-making process when choosing a channel in a “social” multichannel environment that includes social media channels, and the complementary and competitive effects compared to traditional channels within the multichannel strategy of a major European telecoms provider. A conceptual framework of multichannel customer behaviour in a “social” multichannel environment is proposed.

Design/methodology/approach

The study adopts an exploratory approach through 74 semi-structured interviews with customers of a major European telecoms provider who have also used social media channels to contact the company (customer-initiated contact, CIC).

Findings

Users of distinct social media channels are driven by different motivations. For instance, the social motivation for using social media is evident for Facebook users, while Twitter users are mainly driven by utilitarian considerations. Although users of different social media channels represent distinct segments in terms of behaviours and motivations, complementary effects among channels (new and traditional) are generally detected in the sense that a better customer experience is driven by the presence of multiple channels.

Research limitations/implications

Data collection was performed for only one company in one industry and should be extended to other industries, although our results were confirmed by discussions with social media managers of other companies.

Practical implications

The research offers suggestions to develop multichannel strategies in a “social” multichannel environment.

Originality/value

This study advances knowledge in the multichannel management field by investigating why and how customers utilize channels in a multichannel environment that includes social media channels. The authors develop a conceptual framework of multichannel customer behaviour for CIC in a “social” multichannel environment.

Details

European Journal of Marketing, vol. 48 no. 7/8
Type: Research Article
ISSN: 0309-0566

Keywords

Article
Publication date: 2 October 2017

Miriam Muñoz-Expósito, M. Ángeles Oviedo-García and Mario Castellanos-Verdugo

As social media are essentially different from traditional media, due to their social networking structures and egalitarian nature, conventional media metrics are not appropriate…

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Abstract

Purpose

As social media are essentially different from traditional media, due to their social networking structures and egalitarian nature, conventional media metrics are not appropriate. Social media networks have nevertheless become another communications channel that companies use to achieve their marketing goals. Even though the measurement of marketing constructs in social media is elusive, a comprehensive means of measuring engagement is proposed for a successful social media site: Twitter. The paper aims to discuss this issue.

Design/methodology/approach

A measurement for customer engagement based on conceptual reflections is presented in the context of Twitter.

Findings

A new environment fostered by internet obliges companies to manage social media accounts and to assess engagement with company brands. To do so, companies need to analyze engagement trends by means of a metric, helping them to design an appropriate engagement strategy. The proposed metric provides much needed insight for companies to fine-tune their engagement strategy. Moreover, a means of calculating engagement from the parameters that Twitter makes available to the public is also proposed.

Research limitations/implications

The metric for engagement in Twitter that is proposed in this paper will be the starting point for future improvements through a conceptual and empirical discussion on this issue.

Originality/value

This is the first proposal specifically designed for Twitter, to the best of the authors’ knowledge, for measuring engagement.

Details

Internet Research, vol. 27 no. 5
Type: Research Article
ISSN: 1066-2243

Keywords

Article
Publication date: 10 July 2020

Tasos Spiliotopoulos and Ian Oakley

The purpose of this paper is to elaborate on how people navigate the social media ecosystem and how they decide, which social network site (SNS) to use. To this end, the current…

Abstract

Purpose

The purpose of this paper is to elaborate on how people navigate the social media ecosystem and how they decide, which social network site (SNS) to use. To this end, the current study draws from uses and gratifications (U&G) theory to elicit and compare motives for the use of Facebook and Twitter and uses behavioral data to examine the findings in the context of technology non-use.

Design/methodology/approach

An online survey was administered to 232 Facebook users and the results were complemented with 12 usage variables collected via the Facebook application programing interface for the same users. Exploratory factor analysis identified and described the motives for using Facebook and Twitter and multiple regression models examined the relationships between the motives for using the two sites. A multivariate analysis of variance and a series of t-tests investigated the differences in actual behavior between Twitter users and non-users.

Findings

Results suggest that SNS users will use both sites to gratify their need for information, but will only do so for entertainment that has social characteristics. Furthermore, Facebook users that are more embedded in the site and use the site to support their offline life are more likely to also use Twitter.

Practical implications

The paper includes implications for SNS researchers, designers and managers by highlighting the motivational and behavioral differences between users of the two sites and the importance of technological affordances for understanding and explaining SNS selection.

Originality/value

This study extends previous cross-site U&G and non-use research by combining survey and behavioral data.

Details

Journal of Systems and Information Technology, vol. 22 no. 2
Type: Research Article
ISSN: 1328-7265

Keywords

Article
Publication date: 8 January 2021

Milad Mirbabaie, Stefan Stieglitz and Felix Brünker

The purpose of this study is to investigate communication on Twitter during two unpredicted crises (the Manchester bombings and the Munich shooting) and one natural disaster…

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Abstract

Purpose

The purpose of this study is to investigate communication on Twitter during two unpredicted crises (the Manchester bombings and the Munich shooting) and one natural disaster (Hurricane Harvey). The study contributes to understanding the dynamics of convergence behaviour archetypes during crises.

Design/methodology/approach

The authors collected Twitter data and analysed approximately 7.5 million relevant cases. The communication was examined using social network analysis techniques and manual content analysis to identify convergence behaviour archetypes (CBAs). The dynamics and development of CBAs over time in crisis communication were also investigated.

Findings

The results revealed the dynamics of influential CBAs emerging in specific stages of a crisis situation. The authors derived a conceptual visualisation of convergence behaviour in social media crisis communication and introduced the terms hidden and visible network-layer to further understanding of the complexity of crisis communication.

Research limitations/implications

The results emphasise the importance of well-prepared emergency management agencies and support the following recommendations: (1) continuous and (2) transparent communication during the crisis event as well as (3) informing the public about central information distributors from the start of the crisis are vital.

Originality/value

The study uncovered the dynamics of crisis-affected behaviour on social media during three cases. It provides a novel perspective that broadens our understanding of complex crisis communication on social media and contributes to existing knowledge of the complexity of crisis communication as well as convergence behaviour.

Details

Information Technology & People, vol. 35 no. 1
Type: Research Article
ISSN: 0959-3845

Keywords

Book part
Publication date: 4 November 2022

Ismail Shaheer, Neil Carr and Andrea Insch

Social media is noted for its usefulness and contribution to destination marketing and management. Social media data is particularly valued as a source to understand issues such…

Abstract

Social media is noted for its usefulness and contribution to destination marketing and management. Social media data is particularly valued as a source to understand issues such as tourist behavior and destination marketing strategies. Among the social media platforms, Twitter is one of the most utilized in research. Its use raises two issues: the challenge of obtaining historical data and the importance of qualitative data analysis. Regarding these issues, the chapter argues that retrieving tweets using hashtags and keywords on the Twitter website provides a corpus of tweets that is valuable for research, especially for qualitative inquiries. In addition, the value of qualitative analysis of Twitter data is presented, demonstrating, among other things, how such an approach captures in-depth information, enables appreciation and inclusion of the nonconventional language used on social media, distinguishes between “noise” and useful information, and recognizes information as the sum of all parts in the data.

Details

Advanced Research Methods in Hospitality and Tourism
Type: Book
ISBN: 978-1-80117-550-0

Keywords

Article
Publication date: 23 October 2023

Rongying Zhao, Weijie Zhu, He Huang and Wenxin Chen

Social mediametrics is a subfield of measurement in which the emphasis is placed on social media data. This paper analyzes the trends and patterns of paper comprehensively…

Abstract

Purpose

Social mediametrics is a subfield of measurement in which the emphasis is placed on social media data. This paper analyzes the trends and patterns of paper comprehensively mentions on Twitter, with a particular focus on Twitter's mention behaviors. It uncovers the dissemination patterns and impact of academic literature on social media. The research has significant theoretical and practical implications.

Design/methodology/approach

This paper explores the fundamental attributes of Twitter mentions by means of analyzing 9,476 pieces of scholarly literature (5,097 from Nature and 4,379 from Science), 1,474,898 tweets and 451,567 user information collected from Altmetric.com database and Twitter API. The study uncovers assorted Twitter mention characteristics, mention behavior patterns and data accumulation patterns.

Findings

The findings illustrate that the top academic journals on Twitter have a wider range of coverage and display similar distribution patterns to other academic communication platforms. A large number of mentioners remain unidentified, and the distribution of follower counts among the mention users exhibits a significant Pareto effect, indicating a small group of highly influential users who generate numerous mentions. Furthermore, the proportion of sharing and exchange mentions positively correlates with the number of user followers, while the incidence of supportive mentions has a negative correlation. In terms of country-specific mention behavior, Thai scholars tend to utilize supportive mentions more frequently, whereas Korean scholars prefer sharing mentions over communicating mentions. The cumulative pattern of Twitter mentions suggests that these occur before official publication, with a half-life of 6.02 days and a considerable reduction in the number of mentions is observed on the seventh day after publication.

Originality/value

Conducting a multi-dimensional and systematic analysis of Twitter mentions of scholarly articles can aid in comprehending and utilizing social media communication patterns. This analysis can uncover literature's distribution patterns, dissemination effects and social significance in social media.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

1 – 10 of over 10000