Analysis of content strategies of selected brand tweets and its influence on information diffusion

Purpose The purpose of this paper is to design organization message content strategies and analyse their information diffusion on the microblogging website, Twitter. Design/methodology/approach Using data from 29 brands and 9392 tweets, message strategies on twitter are classified into four strategies. Using content analysis all the tweets are classified into informational strategy, transformational strategy, interactional strategy and promotional strategy. Additionally, the information diffusion for the developed message strategies was explored. Furthermore, message content features such as text readability features, language features, Twitter-specific features, vividness features on information diffusion are analysed across message strategies. Additionally, the interaction between message strategies and message features was carried out. Findings Finding reveals that informational strategies were the dominant message strategy on Twitter. The influence of text readability features language features, Twitter-specific features, vividness features that influenced information diffusion varied across four message strategies. Originality/value This study offers a completely novel way for effectively analysing information diffusion for branded tweets on Twitter and can show a path to both researchers and practitioners for the development of successful social media marketing strategies

Dialogic interaction with diversified audiences in Twitter for research dissemination purposes

International research groups are expected to ensure global dissemination and visibility of their knowledge production, for which Twitter is effectively employed to reach diversified audiences. This paper analyses the dialogic dimension of tweets published in accounts of Horizon2020 research projects, where group’s productivity and work are promoted, and multiple readers addressed. Our study focuses on the use, in these Twitter accounts, of interactional pragmatic strategies, their verbal realisation through engagement markers, as well as on medium affordances and non-verbal markers. A sample of 1 454 tweets from 10 accounts of the EUROPROtweets corpus were coded and analysed through NVivo. The data-driven pragmatic analysis triggered the identification of 8 interactional strategies. We then quantitatively analysed the use of engagement makers and qualitatively studied the characteristic non-verbal markers with a dialogic function within each of these. Our findings will help understand the complexities of current digital academic professional practices, especially as regards the dynamics of dialogic interaction in social media. © 2022 Universidad Complutense de Madrid

Interaction and transformation on social media: the case of Twitter campaigns

The increasing popularity of social media platforms creates new digital social networks in which individuals can interact and share information, news, and opinion. The use of these technologies appears to have the capacity to transform current social configurations and relations, not least within the public and civic spheres. Within the social sciences, much emphasis has been placed on conceptualizing social media’s role in modern society and the interrelationships between online and offline actors and events. In contrast, little attention has been paid to exploring user practices on social media and how individual posts respond to each other. To demonstrate the value of an interactional approach toward social media analysis, we performed a detailed analysis of Twitter-based online campaigns. After categorizing social media posts based on action(s), we developed a typology of user exchanges. We found these social media campaigns to be highly heterogeneous in content, with a wide range of actions performed and substantial numbers of tweets not engaged with the substance of the campaign. We argue that this interactional approach can form the basis for further work conceptualizing the broader impact of activist campaigns and the treatment of social media as “data” more generally. In this way, analytic focus on interactional practices on social media can provide empirical insight into the micro-transformational characteristics within “campaign communication.

Participation as a tool for interactional work on Twitter: A sociolinguistic approach to social media 'engagement'

This work approaches the concept of social media engagement through a lens of participation theory. Following the work of Goffman (1981) and others, this dissertation uses the concepts of the participation framework and the participant role to explore engagement as a function of participation in interaction. The purposes of this dissertation are three-fold: to model participant roles as they are built in interaction on Twitter, to discover the ways in which participation is established through the linguistic choices enacted by participants, and to demonstrate the role of the medium as an important factor influencing possibilities for participation. Using discourse analysis as a methodology, tweets from accounts associated with National Hockey League (NHL) organizations are analyzed for the linguistic resources that are used to reference interactional roles traditionally understood as “speaker” and “hearer”. In turn, the linguistic and discursive resources deployed in team tweets are used to reveal these speaker and hearer roles as more detailed and complex production and reception frameworks. The modal affordances of Twitter are also investigated as to their role in influencing the building of participation frameworks through talk, including unique linguistic forms that are available to Twitter users and possibilities for hiding or revealing participants through the Twitter screen. The findings of this investigation reveal three primary models for production frameworks for NHL accounts: an Impersonal Model that eschews identification of the parties in production roles, an Interpersonal Model that highlights the individuals involved in the interaction, and a Team Model that obscures the individual to focus on the team or organization as a primary participant. Additionally, a framework for understanding recipient audiences on Twitter is proposed, incorporating both actual and intended audiences. Consistent patterns in the language choices used to construct participatory identities for production and reception roles are demonstrated, highlighting the value of using linguistic data as a resource for investigations of participation. Finally, Twitter’s modal affordances are shown to be an integral part of the ways that users enact participatory concepts, such as co-presence and address, revealing the importance of considering the role of the medium in participation studies

A linguistically-driven methodology for detecting impending and unfolding emergencies from social media messages

Natural disasters have demonstrated the crucial role of social media before, during and after emergencies (Haddow & Haddow 2013). Within our EU project Sland \ub4 ail, we aim to ethically improve \ub4 the use of social media in enhancing the response of disaster-related agen-cies. To this end, we have collected corpora of social and formal media to study newsroom communication of emergency management organisations in English and Italian. Currently, emergency management agencies in English-speaking countries use social media in different measure and different degrees, whereas Italian National Protezione Civile only uses Twitter at the moment. Our method is developed with a view to identifying communicative strategies and detecting sentiment in order to distinguish warnings from actual disasters and major from minor disasters. Our linguistic analysis uses humans to classify alert/warning messages or emer-gency response and mitigation ones based on the terminology used and the sentiment expressed. Results of linguistic analysis are then used to train an application by tagging messages and detecting disaster- and/or emergency-related terminology and emotive language to simulate human rating and forward information to an emergency management system

Using text-mining-assisted analysis to examine the applicability of unstructured data in the context of customer complaint management

Double DegreeIn quest of gaining a more holistic picture of customer experiences, many companies are starting to consider textual data due to the richer insights on customer experience touch points it can provide. Meanwhile, recent trends point towards an emerging integration of customer relationship management and customer experience management and thereby availability of additional sources of textual data. Using text-mining-assisted analysis, this study demonstrates the practicality of the arising opportunity with means of perceived justice theory in the context of customer complaint management. The study shows that customers value interpersonal aspects most as part of the overall complaint handling process. The results link the individual factors in a sequence of ‘courtesy → interactional justice → satisfaction with complaint handling’, followed by behavioural outcomes. Academic and managerial implications are discussed

Digitizing Sacks? Approaching social media as data

During the course of this article, we explore ethnomethodological principles in relation to approaching social media as data. More specifically, we consider the extent to which the work of Harvey Sacks and his rich intellectual legacy might inform this nascent field of empirical inquiry. This exploration is realised in the context of interdisciplinary research at the interface of social and computational science. Drawing from an extensive range of empirical projects into social media we reflect on the efficacy and limitations of these principles (Sacks, 1992) for understanding social media interaction as open data and practical action in the digital age

Computational Sociolinguistics: A Survey

Language is a social phenomenon and variation is inherent to its social nature. Recently, there has been a surge of interest within the computational linguistics (CL) community in the social dimension of language. In this article we present a survey of the emerging field of "Computational Sociolinguistics" that reflects this increased interest. We aim to provide a comprehensive overview of CL research on sociolinguistic themes, featuring topics such as the relation between language and social identity, language use in social interaction and multilingual communication. Moreover, we demonstrate the potential for synergy between the research communities involved, by showing how the large-scale data-driven methods that are widely used in CL can complement existing sociolinguistic studies, and how sociolinguistics can inform and challenge the methods and assumptions employed in CL studies. We hope to convey the possible benefits of a closer collaboration between the two communities and conclude with a discussion of open challenges.Comment: To appear in Computational Linguistics. Accepted for publication: 18th February, 201

Metadiscourse analysis of digital interpersonal interactions in academic settings in Turkey

Rapid technological advances, efficiency and easy access have firmly established emailing as a vital medium of communication in the last decades. Nowadays, all around the world, particularly in educational settings, the medium is one of the most widely used modes of interaction between students and university lecturers. Despite their important role in academic life, very little is known about the metadiscursive characteristics of these e-messages and as far as the author is aware there is no study that has examined metadiscourse in request emails in Turkish. This study aims to contribute to filling in this gap by focusing on the following two research questions: (i) How many and what type of interpersonal metadiscourse markers are used in request emails sent by students to their lecturers? (ii) Where are they placed and how are they combined with other elements in the text? In order to answer these questions a corpus of unsolicited request e-mails in Turkish was compiled. The data collection started in January 2010 and continued until March 2018. A total of 353 request emails sent from university students to their lecturers were collected. The data were first transcribed in CLAN CHILDES format and analysed using the interpersonal model. The metadiscourse categories that aimed to involve readers in the email were identified and classified. Next, their places in the text were determined and described in detail. Findings of the study show that request emails include a wide array of multifunctional interpersonal metadiscourse markers which are intricately combined and employed by the writers to reach their aims. The results also showed that there is a close relation between the “weight of the request” and number of the interpersonal metadiscourse markers in request mails

Microcelebrity Practices: A Cross-Platform Study Through a Richness Framework

Social media have introduced a contemporary shift from broadcast to participatory media, which has brought about major changes to the celebrity management model. It is now common for celebrities to bypass traditional mass media and take control over their promotional discourse through the practice of microcelebrity. The theory of microcelebrity explains how people turn their public persona into media content with the goal of gaining and maintaining audiences who are regarded as an aggregated fan base. To accomplish this, the theory suggests that people employ a set of online self-presentation techniques that typically consist of three core practices: identity constructions, fan interactions and promoting visibility beyond the existing fan base. Studies on single platforms (e.g., Twitter), however, show that not all celebrities necessarily engage in all core practices to the same degree. Importantly, celebrities are increasingly using multiple social media platforms simultaneously to expand their audience, while overcoming the limitations of a particular platform. This points to a gap in the literature and calls for a cross-platform study. This dissertation employed a mixed-methods research design to reveal how social media platforms i.e., Twitter and Instagram, helped celebrities grow and maintain their audience. The first phase of the study relied on a richness scoring framework that quantified social media activities using affordance richness, a measure of the ability of a post to deliver the information necessary in affording a celebrity to perform an action by using social media artifacts. The analyses addressed several research questions regarding social media uses by different groups of celebrities and how the audience responded to different microcelebrity strategies. The findings informed the design of the follow-up interviews with audience members. Understanding expectations and behaviors of fans is relevant not only as a means to enhance the practice’s outcome and sustain promotional activity, but also as a contribution to our understandings about contemporary celebrity-fans relationships mediated by social media. Three findings are highlighted. First, I found that celebrities used the two platforms differently, and that different groups of celebrities emphasized different core practices. This finding was well explained by the interviews suggesting that the audiences had different expectations from different groups of celebrities. Second, microcelebrity strategies played an important role in an audience’s engagement decisions. The finding was supported by the interviews indicating that audience preferences were based on some core practices. Lastly, while their strategies had no effect on follow and unfollow decisions, the consistency of the practices had significant effects on the decisions. This study makes contributions to the theory of Microcelebrity and offers practical contributions by providing broad insights from both practitioners’ and audiences’ perspectives. This is essential given that microcelebrity is a learned practice rather than an inborn trait