A framework based on Twitter and big data analytics to enhance sustainability performance

Queiroz, Maciel M.

doi:10.1002/tqem.21576

Cited by 8 publications

(8 citation statements)

References 13 publications

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“…For instance, scholars have pointed out that shorter posts typically lead to a higher engagement rate on Facebook (Sabate et al, 2014), potentially because concise messages reduce the amount of cognitive effort needed for information processing (She et al, 2022). Across the various available types of platforms, Twitter, in particular, restricts each post to a maximum of 280 characters (Queiroz, 2018), and although these short and unstructured posts conform with social media practice, they increase the complexity for algorithms to make sense of digital interaction. Common challenges arise from using compound words, acronyms, and ungrammatical sentences (Ariffin and Tiun, 2020).…”

Section: Topic Modeling As a Solution To Cope With Unstructured Text ...mentioning

confidence: 99%

A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts

Egger

2022

Front. Sociol.

356

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The richness of social media data has opened a new avenue for social science research to gain insights into human behaviors and experiences. In particular, emerging data-driven approaches relying on topic models provide entirely new perspectives on interpreting social phenomena. However, the short, text-heavy, and unstructured nature of social media content often leads to methodological challenges in both data collection and analysis. In order to bridge the developing field of computational science and empirical social research, this study aims to evaluate the performance of four topic modeling techniques; namely latent Dirichlet allocation (LDA), non-negative matrix factorization (NMF), Top2Vec, and BERTopic. In view of the interplay between human relations and digital media, this research takes Twitter posts as the reference point and assesses the performance of different algorithms concerning their strengths and weaknesses in a social science context. Based on certain details during the analytical procedures and on quality issues, this research sheds light on the efficacy of using BERTopic and NMF to analyze Twitter data.

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Section: Topic Modeling As a Solution To Cope With Unstructured Text ...mentioning

confidence: 99%

A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts

Egger

2022

Front. Sociol.

356

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“…Over the latest decades, social media platforms allow users a wide spectrum of digital interaction and information exchange, producing overwhelming sets of user-generated Big Data [1]. Environmental management and sustainability topics have been widely analyzed with Big Data Analytics techniques to reveal hidden trends and patterns in public perceptions, mostly utilizing data from the Twitter microblogging service [2][3][4]. The impact of climate change becomes more evident to society and the economy at scales ranging from global to local.…”

Section: Introductionmentioning

confidence: 99%

Exploring climate change on Twitter using seven aspects: Stance, sentiment, aggressiveness, temperature, gender, topics, and disasters

Effrosynidis

Sylaïos²,

Arampatzis³

2022

PLoS ONE

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How do climate change deniers differ from believers? Is there any correlation between human sentiment and deviations from historic temperature? We answer nine such questions using 13 years of Twitter data and 15 million tweets. Seven aspects are explored, namely, user gender, climate change stance and sentiment, aggressiveness, deviations from historic temperature, topics discussed, and environmental disaster events. We found that: a) climate change deniers use the term global warming much often than believers and use aggressive language, while believers tweet more about taking actions to fight the phenomenon, b) deniers are more present in the American Region, South Africa, Japan, and Eastern China and less present in Europe, India, and Central Africa, c) people connect much more the warm temperatures with man-made climate change than cold temperatures, d) the same regions that had more climate change deniers also tweet with negative sentiment, e) a positive correlation is observed between human sentiment and deviations from historic temperature; when the deviation is between −1.143°C and +2.401°C, people tweet the most positive, f) there exist 90% correlation between sentiment and stance, and -94% correlation between sentiment and aggressiveness, g) no clear patterns are observed to correlate sentiment and stance with disaster events based on total deaths, number of affected, and damage costs, h) topics discussed on Twitter indicate that climate change is a politicized issue and people are expressing their concerns especially when witnessing extreme weather; the global stance could be considered optimistic, as there are many discussions that point out the importance of human intervention to fight climate change and actions are being taken through events to raise the awareness of this phenomenon.

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“…Knowledge sharing enables data to be collected in more volumes and velocity from various sources (Queiroz, 2018; Rinaldi & Russo, 2020), while the classification and simplifying of these data makes it easier to process. Data whose source, content and properties are verified may become a valuable business model, process or method, even encouraging new products or services, which shows the benefits of knowledge sharing.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Big data and innovative organizational performance: Evidence from a moderated‐mediated model

Demir

YAŞAR

2022

Creat Innov Manage

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Big data in hotels is crucial in new business models, processes and methods for improving innovative organizational performance. This study investigates how big data and its sharing directly impact innovative organizational performance through big data analytics capabilities. Research data collected from 438 participants at 36 five-star hotels were analysed using structural equation models. The analysis found that using and sharing big data in hotels directly affects big data analytics capabilities and innovative organizational performance. Furthermore, analytical capacities mediate between using and sharing big data and creative organizational performance.These results have some theoretical and practical implications.

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A framework based on Twitter and big data analytics to enhance sustainability performance

Cited by 8 publications

References 13 publications

A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts

A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts

Exploring climate change on Twitter using seven aspects: Stance, sentiment, aggressiveness, temperature, gender, topics, and disasters

Big data and innovative organizational performance: Evidence from a moderated‐mediated model

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