Effects of promotion tweets on the number of followers in micro-blogging site

Liu, Yi; Tarigan, Bernadetta

doi:10.1145/2971603.2971605

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…A previous study measured the success of a seller based on the followers' number [11]. To increase the number of followers, participants tend to use hashtags and advertisements, which was also shown by a previous study, which promoted on Twitter and found it to increase the followers' number [36]. Additionally, participants try to have an active account with social interaction.…”

Section: Discussionmentioning

confidence: 75%

Investigating Commercial Capabilities and Trust in Social Media Applications for Entrepreneurs

AlArfaj

Solaiman

2019

Proceedings of the 9th International Conference on Communities &Amp; Technologies - Transforming Communities

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This study attempts to present sellers' behaviours and activities in social commerce within the context of a local social group. It describes how the sale and marketing of homemade products, or imported goods, are conducted in Saudi Arabia using social media platforms (Instagram, WhatsApp, Twitter, and Snapchat) as well as using offline tools such as phones, family and friend recommendations, and events. We interviewed 17 female entrepreneurs who own e-shops on social media applications. The research describes how sellers try to market themselves and build their reputation to gain consumer trust despite a lack of commercial functionality within the social platforms that they use. This paper presents insights into new opportunities for peers and business owners that social commerce can bring. We also argue that social media applications can expand their uptake from businesses and entrepreneurs by designing functionality aimed at improving their commercial capabilities, and aimed at enabling sellers to build their own reputation and trust. CCS CONCEPTS• CCS → Human-centered computing → Human computer interaction (HCI) → Interaction techniques

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Section: Discussionmentioning

confidence: 75%

Investigating Commercial Capabilities and Trust in Social Media Applications for Entrepreneurs

AlArfaj

Solaiman

2019

Proceedings of the 9th International Conference on Communities &Amp; Technologies - Transforming Communities

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“…Specifically, those who identify as morning people tend to experience the highest level of alertness during the early hours of the day, while evening people exhibit peak alertness later in the day. Prior works [145,146] have also shown that the popularity of a social media post depends on the time of its publication. Publishing content on a social media platform at times when the highest number of users are logged in and using the platform would ensure that the content receives the highest attention from the global audience in terms of views and engagement, which is expected to have a positive impact on sales.…”

Section: Discussionmentioning

confidence: 99%

A Comprehensive Analysis and Investigation of the Public Discourse on Twitter about Exoskeletons from 2017 to 2023

Thakur,

Patel,

Poon

et al. 2023

Future Internet

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Exoskeletons have emerged as a vital technology in the last decade and a half, with diverse use cases in different domains. Even though several works related to the analysis of Tweets about emerging technologies exist, none of those works have focused on the analysis of Tweets about exoskeletons. The work of this paper aims to address this research gap by presenting multiple novel findings from a comprehensive analysis of about 150,000 Tweets about exoskeletons posted between May 2017 and May 2023. First, findings from temporal analysis of these Tweets reveal the specific months per year when a significantly higher volume of Tweets was posted and the time windows when the highest number of Tweets, the lowest number of Tweets, Tweets with the highest number of hashtags, and Tweets with the highest number of user mentions were posted. Second, the paper shows that there are statistically significant correlations between the number of Tweets posted per hour and the different characteristics of these Tweets. Third, the paper presents a multiple linear regression model to predict the number of Tweets posted per hour in terms of these characteristics of Tweets. The R2 score of this model was observed to be 0.9540. Fourth, the paper reports that the 10 most popular hashtags were #exoskeleton, #robotics, #iot, #technology, #tech, #innovation, #ai, #sci, #construction and #news. Fifth, sentiment analysis of these Tweets was performed, and the results show that the percentages of positive, neutral, and negative Tweets were 46.8%, 33.1%, and 20.1%, respectively. To add to this, in the Tweets that did not express a neutral sentiment, the sentiment of surprise was the most common sentiment. It was followed by sentiments of joy, disgust, sadness, fear, and anger, respectively. Furthermore, hashtag-specific sentiment analysis revealed several novel insights. For instance, for almost all the months in 2022, the usage of #ai in Tweets about exoskeletons was mainly associated with a positive sentiment. Sixth, lexicon-based approaches were used to detect possibly sarcastic Tweets and Tweets that contained news, and the results are presented. Finally, a comparison of positive Tweets, negative Tweets, neutral Tweets, possibly sarcastic Tweets, and Tweets that contained news is presented in terms of the different characteristic properties of these Tweets. The findings reveal multiple novel insights related to the similarities, variations, and trends of character count, hashtag usage, and user mentions in such Tweets during this time range.

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A Comprehensive Analysis of the Public Discourse on Twitter about Exoskeletons from 2017 to 2023

Thakur,

Patel,

Poon

et al. 2023

Preprint

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The work of this paper presents multiple novel findings from a comprehensive analysis of about 150,000 tweets about exoskeletons posted between May 2017 and May 2023. First, findings from content analysis and temporal analysis of these tweets reveal the specific months per year when a significantly higher volume of Tweets was posted and the time windows when the highest number of tweets, the lowest number of tweets, tweets with the highest number of hashtags, and tweets with the highest number of user mentions were posted. Second, the paper shows that there are statistically significant correlations between the number of tweets posted per hour and different characteristics of these tweets. Third, the paper presents a multiple linear regression model to predict the number of tweets posted per hour in terms of these characteristics of tweets. The R2 score of this model was observed to be 0.9540. Fourth, the paper reports that the 10 most popular hashtags were #exoskeleton, #robotics, #iot, #technology, #tech #innovation, #ai, #sci, #construction and #news. Fifth, sentiment analysis of these tweets was performed using VADER and the DistilRoBERTa-base library. The results show that the percentage of positive, neutral, and negative tweets were 46.8%, 33.1%, and 20.1%, respectively. The results also show that in the tweets that did not express a neutral sentiment, the sentiment of surprise was the most common sentiment. It was followed by the sentiments of joy, disgust, sadness, fear, and anger. Furthermore, analysis of hashtag-specific sentiments revealed several novel insights, for instance, for almost all the months in 2022, the usage of #ai in tweets about exoskeletons was mainly associated with a positive sentiment. Sixth, text processing-based approaches were used to detect possibly sarcastic tweets and tweets that contained news. Finally, a comparison of positive tweets, negative tweets, neutral tweets, possibly sarcastic tweets, and tweets that contained news, in terms of different characteristic properties of these tweets are presented. The findings reveal multiple novel insights, for instance, the average number of hashtags used in tweets that contained news has considerably increased since January 2022.

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Effects of promotion tweets on the number of followers in micro-blogging site

Cited by 3 publications

References 20 publications

Investigating Commercial Capabilities and Trust in Social Media Applications for Entrepreneurs

Investigating Commercial Capabilities and Trust in Social Media Applications for Entrepreneurs

A Comprehensive Analysis and Investigation of the Public Discourse on Twitter about Exoskeletons from 2017 to 2023

A Comprehensive Analysis of the Public Discourse on Twitter about Exoskeletons from 2017 to 2023

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