Social media buzz created by #nanotechnology: insights from Twitter analytics

Singh, Prabhsimran; Kahlon, Karanjeet Singh; Sawhney, Ravinder Singh; Vohra, Rajan; Kaur, Sukhmanjit

doi:10.1515/ntrev-2018-0053

Cited by 12 publications

(7 citation statements)

References 44 publications

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“…With a similar approach, Singh et al found that there are many positive sentiments associated with the subject nanotechnology, such as trust in the technology, anticipation about the outcome, and joy about the availability of the predicted applications, which far outweigh the anger associated with nanowaste, mistrust about failures to meet targets, and anger associated with wasting tons of taxpayers' money on nanotechnology projects. 61 …”

Section: Discussionmentioning

confidence: 99%

The risk perception of nanotechnology: evidence from twitter

et al. 2022

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Section: Discussionmentioning

confidence: 99%

The risk perception of nanotechnology: evidence from twitter

et al. 2022

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“… Data Collection: The collection of data always remains the most crucial part of any research as it forms the fundamental of a sustained foundation of the entire research work (Stieglitz et al, 2018 , 2020 ; Singh et al, 2018a ). Hence, Twitter API was integrated into the R-language script to retrieve data (tweets) from Twitter in an authenticated manner.…”

Section: Methodsmentioning

confidence: 99%

Is #SDG13 Trending Online? Insights from Climate Change Discussions on Twitter

et al. 2022

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Anthropogenic activities over the past few decades have led to increased vulnerability of environmental and ecological stability on this planet. Accelerated climate change is one such subset of the environmental problems that threatens the very existence of humankind in twenty first century. Governments, United Nations (UN) and other humanitarian agencies across the globe have developed and devised strategies for climate action that requires grater public awareness and actions. Social media has played a vital role in information dissemination and raising public awareness of climate change in the digital era. To this aid, an upsurge has been documented in recent times regarding discussions over climate change with #SDG13 (Sustainable Development Goals) at its epicenter. Following the principles of Actor Network Theory (ANT) we analyzed a large volume of Twitter data to understand general citizens’ perception and attitude towards climate change. Our findings unveil people’s opinion on causes and concerns related to barriers of adopting a more sustainable consumption and lifestyle practice. There is also a growing apathy towards sluggish government actions that makes little difference. People were also found to exchange innovative concepts and measures towards mitigating the effects of climate change.

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“…al., 2018a). The descriptive analysis gives descriptive statistics about number of tweets, number of tweet senders, hashtags, @mentions, word cloud etc (Chae, 2015;Ganis and Kohirkar, 2015;Purohit et al, 2013;Singh et al, 2018b).…”

Section: Endmentioning

confidence: 99%

Can twitter analytics predict election outcome? An insight from 2017 Punjab assembly elections

Singh

Dwivedi

Kahlon

et al. 2020

Government Information Quarterly

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Since the beginning of this decade, there has seen an exponential growth in number of internet users using social media, especially Twitter for sharing their views on various topics of common interest like sports, products, politics etc. Due to the active participation of large number of people on Twitter, huge amount of data (i.e. big data) is being generated, which can be put to use (after refining) to analyze real world problems. This paper takes into consideration the Twitter data related to the 2017 Punjab (a state of India) assembly elections and applies different social media analytic techniques on collected tweets to extract and unearth hidden but useful information. In addition to this, we have employed machine learning algorithm to perform polarity analysis and have proposed a new seat forecasting method to accurately predict the number of seats that a political party is likely to win in the elections. Our results confirmed that Indian National Congress was likely to emerge winner and that in fact was the outcome, when results got declared.

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Social media buzz created by #nanotechnology: insights from Twitter analytics

Cited by 12 publications

References 44 publications

The risk perception of nanotechnology: evidence from twitter

The risk perception of nanotechnology: evidence from twitter

Is #SDG13 Trending Online? Insights from Climate Change Discussions on Twitter

Can twitter analytics predict election outcome? An insight from 2017 Punjab assembly elections

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