TY - GEN
T1 - A methodology to characterize and compute public perception via social networks
AU - Bibi, Shaista
AU - Hussain, Shahid
AU - Ahmed, Mansoor
AU - Zeb, Muhammad Shahid
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - Literature shows that the business experts and the data scientist always look at new technologies and its impact on their data centers. Nowadays, in terms of green computing, Internet of Things (IoT), Artificial Intelligence (AI), and Virtual/Augmented Reality (V/AR) are considered and adapted as new technologies. Though, in numerous studies, individual impact of each technology is investigated and reported. However, to the best of our knowledge, there exists no such study that describes the public sentiments and perception regarding V/AR, IoT, and AI; that are required to understand the public demand and improve the business process. In this paper, we propose a computation method for the public perception of new technology(y/ies) in various aspects. Topic modeling, sentiment analysis, and statistical techniques are applied to make the proposed method functional. Subsequently, we have performed a case study, that comprises on 147 million public tweets extracted from the Twitter social network. Moreover, our main contributions are related to the understanding of, (1) Distribution, (2) public perception, and (3) correlation of IoT, AI, and V/AR. The main outcome of the proposed study are; (1) More tweets on AI (51.51%) rather than V/AR (18.37%) and IoT (30.11%), (2) positive comments for IoT and negative comments are identified via sentiment analysis. (3) Some of the noteworthy terms found are blockchain, futurist, user-experience, users-demand, bonus, and presale. These all have been identified as sub-topics for each keyword describing the mutual relationship among the topics. This study is easy to replicate in terms of adaptation of new technology(y/ies) for sustainability and evolution of business process and data centers on the basis of public perception.
AB - Literature shows that the business experts and the data scientist always look at new technologies and its impact on their data centers. Nowadays, in terms of green computing, Internet of Things (IoT), Artificial Intelligence (AI), and Virtual/Augmented Reality (V/AR) are considered and adapted as new technologies. Though, in numerous studies, individual impact of each technology is investigated and reported. However, to the best of our knowledge, there exists no such study that describes the public sentiments and perception regarding V/AR, IoT, and AI; that are required to understand the public demand and improve the business process. In this paper, we propose a computation method for the public perception of new technology(y/ies) in various aspects. Topic modeling, sentiment analysis, and statistical techniques are applied to make the proposed method functional. Subsequently, we have performed a case study, that comprises on 147 million public tweets extracted from the Twitter social network. Moreover, our main contributions are related to the understanding of, (1) Distribution, (2) public perception, and (3) correlation of IoT, AI, and V/AR. The main outcome of the proposed study are; (1) More tweets on AI (51.51%) rather than V/AR (18.37%) and IoT (30.11%), (2) positive comments for IoT and negative comments are identified via sentiment analysis. (3) Some of the noteworthy terms found are blockchain, futurist, user-experience, users-demand, bonus, and presale. These all have been identified as sub-topics for each keyword describing the mutual relationship among the topics. This study is easy to replicate in terms of adaptation of new technology(y/ies) for sustainability and evolution of business process and data centers on the basis of public perception.
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U2 - 10.1007/978-3-030-16187-3_49
DO - 10.1007/978-3-030-16187-3_49
M3 - Conference contribution
AN - SCOPUS:85065062460
SN - 9783030161866
T3 - Advances in Intelligent Systems and Computing
SP - 500
EP - 510
BT - New Knowledge in Information Systems and Technologies - Volume 3
A2 - Adeli, Hojjat
A2 - Reis, Luís Paulo
A2 - Costanzo, Sandra
A2 - Rocha, Álvaro
PB - Springer Verlag
T2 - World Conference on Information Systems and Technologies, WorldCIST 2019
Y2 - 16 April 2019 through 19 April 2019
ER -