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Data analytics of social media publicity to enhance household waste management

Jiang, Peng, Fan, Yee Van, Klemeš, Jiří Jaromír·2021·Resources, Conservation and Recycling
DOI 10.1016/j.resconrec.2020.105146PMC PMC7462838
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Research works printed but not linked: 43

  1. Agrawal, 2018, What is wrong with topic modeling? and how to fix it using search-based software engineering, Inf. Softw. Technol., 98, 74, 10.1016/j.infsof.2018.02.005 · DOI
  2. Akaike, 2011, Akaike’s information criterion, Int. Encycl. Stat. Sci., 10.1007/978-3-642-04898-2_110 · DOI
  3. Blei, 2003, Latent Dirichlet allocation, J. Mach. Learn. Res., 3, 993
  4. Cole, 2016, Communications: social media and the waste management sector: eight strategies to use social media more effectively, Waste Adv. Mag.
  5. Cui, 2018, The operational value of social media information, Prod. Oper. Manag., 27, 1749, 10.1111/poms.12707 · DOI
  6. Desgagné, 2019, Bayesian robustness to outliers in linear regression and ratio estimation, Braz. J. Probabi. Stat., 33, 205
  7. Doane, 2011, Measuring skewness: a forgotten statistic?, J. Stat. Educ., 19, 1, 10.1080/10691898.2011.11889611 · DOI
  8. Eriksen, 2018, Contamination in plastic recycling: influence of metals on the quality of reprocessed plastic, Waste Manag., 79, 595, 10.1016/j.wasman.2018.08.007 · DOI · Paper page
  9. Fan, 2020, An update of COVID-19 influence on waste management, Sci. Total Environ., 142014
  10. Franses, 2015, The life cycle of social media, Appl. Econ. Lett., 22, 796, 10.1080/13504851.2014.978069 · DOI
  11. Frempong, 2020, The relationship among customer operant resources, online value co-creation and electronic-word-of-mouth in solid waste management marketing, J. Clean. Prod., 248, 10.1016/j.jclepro.2019.119228 · DOI
  12. Frigge, 1989, Some implementations of the boxplot, Am. Stat., 43, 50, 10.1080/00031305.1989.10475612 · DOI
  13. Gaenssle, 2020, Stars in social media: new light through old windows?, J. Media Bus. Stud.
  14. Gu, 2015, Characterization, quantification and management of household solid waste: a case study in China, Resour. Conserv. Recycl., 98, 67, 10.1016/j.resconrec.2015.03.001 · DOI
  15. Gurcan, 2019, Big data software engineering: analysis of knowledge domains and skill sets using LDA-based topic modeling, IEEE Access, 7, 82541, 10.1109/ACCESS.2019.2924075 · DOI
  16. Hu, 2017, Click “like” on Facebook: the effect of customer-to-customer interaction on customer voluntary performance for social networking sites, Int. J. Hum.–Comput. Interact., 33, 135, 10.1080/10447318.2016.1221203 · DOI
  17. Jelodar, 2019, Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a survey, Multimed. Tools Appl., 78, 15169, 10.1007/s11042-018-6894-4 · DOI
  18. Jiang, 2020, Data-driven analytical framework for waste-dumping behaviour analysis to facilitate policy regulations, Waste Manag., 103, 285, 10.1016/j.wasman.2019.12.041 · DOI
  19. Jiang, 2016, Hidden Markov model for municipal waste generation forecasting under uncertainties, Eur. J. Oper. Res., 250, 639, 10.1016/j.ejor.2015.09.018 · DOI
  20. Jiang, 2019, What prompts users to click on news headlines? Evidence from unobtrusive data analysis, Aslib J. Inf. Manag., 72, 49, 10.1108/AJIM-04-2019-0097 · DOI
  21. Jing, 2016, A study on influential factors of WeChat public accounts information transmission hotness (In Chinese), J. Intell., 35, 157
  22. Klemeš, 2020, The energy and environmental footprints of COVID-19 fighting measures – PPE, disinfection, supply chains, Energy, 10.1016/j.energy.2020.118701 · DOI
  23. Klemeš, 2020, Plastics: friends or foes? The circularity and plastic waste footprint, Energy Sources Part A
  24. Klemeš, 2020, Minimising the present and future plastic waste, energy and environmental footprints related to COVID-19, Renew. Sustain. Energy Rev., 127, 10.1016/j.rser.2020.109883 · DOI
  25. Knickmeyer, 2019, Social factors influencing household waste separation: a literature review on good practices to improve the recycling performance of urban areas, J. Clean. Prod.
  26. Krounbi, 2019, Biological and thermochemical conversion of human solid waste to soil amendments, Waste Manag., 89, 366, 10.1016/j.wasman.2019.04.010 · DOI
  27. Ksiazek, 2016, User engagement with online news: conceptualizing interactivity and exploring the relationship between online news videos and user comments, New Media Soc., 18, 502, 10.1177/1461444814545073 · DOI
  28. Lin, 2017, Taking a global view on brand post popularity: six social media brand post practices for global markets, Bus. Horiz., 60, 621, 10.1016/j.bushor.2017.05.006 · DOI
  29. Mallick, 2019, Impact of social media on environmental awareness, environmental awareness and the role of social media, IGI Global, 140
  30. Meinshausen, 2006, Quantile regression forests, J. Mach. Learn. Res., 7, 983
  31. Mintz, 2019, What predicts household waste management behaviors? Culture and type of behavior as moderators. Resources, Conserv. Recycl., 145, 11, 10.1016/j.resconrec.2019.01.045 · DOI
  32. Sarc, 2019, Digitalisation and intelligent robotics in value chain of circular economy oriented waste management–a review, Waste Manag., 95, 476, 10.1016/j.wasman.2019.06.035 · DOI
  33. Sujata, 2019, The role of social media on recycling behaviour, Sustain. Prod. Consum., 20, 365, 10.1016/j.spc.2019.08.005 · DOI
  34. Sun, 2020, Residents’ sentiments towards electricity price policy: evidence from text mining in social media, Resour. Conserv. Recycl., 160, 10.1016/j.resconrec.2020.104903 · DOI
  35. Wamuyu, 2018, Leveraging Web 2.0 technologies to foster collective civic environmental initiatives among low-income urban communities, Comput. Human. Behav., 85, 1, 10.1016/j.chb.2018.03.029 · DOI
  36. Wang, 2020, Engagement factors for waste sorting in China: the mediating effect of satisfaction, J. Clean. Prod., 267, 10.1016/j.jclepro.2020.122046 · DOI
  37. Wang, 2018, How does information publicity influence residents’ behaviour intentions around e-waste recycling?, Resour. Conserv. Recycl., 133, 1, 10.1016/j.resconrec.2018.01.014 · DOI · Paper page
  38. 2015, The Last Word: does social media have a place in improving bin behaviour?, Waste Manag. Review (WMR)
  39. Xiao, 2020, An overview of the municipal solid waste management modes and innovations in Shanghai, China, Environ. Sci. Pollut. Res., 10.1007/s11356-020-09398-5 · DOI · Paper page
  40. Zamri, 2019, Delivery, impact and approach of household food waste reduction campaigns, J. Clean. Prod.
  41. Zhang, 2019, Short-term forecasting and uncertainty analysis of wind turbine power based on long short-term memory network and Gaussian mixture model, Appl. Energy, 241, 229, 10.1016/j.apenergy.2019.03.044 · DOI
  42. Zorpas, 2020, Strategy development in the framework of waste management, Sci. Total Environ., 716, 10.1016/j.scitotenv.2020.137088 · DOI
  43. Zuo, 2020, Sustaining WEEE collection business in China: the case of online to offline (O2O) development strategies, Waste Manag., 101, 222, 10.1016/j.wasman.2019.10.008 · DOI

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Metadata

Authors
Jiang, P., Fan, Y. V., & Klemeš, J. J.
Venue
Resources, Conservation and Recycling
Publisher
Elsevier BV
Published
2021-01
Volume
164
Pages
105146
ISSN
0921-3449
DOI
10.1016/j.resconrec.2020.105146
PMC
PMC7462838
Cited by
73
References
4
Language
en
Licence
Funders
  • Ministerstvo Školství, Mládeže a Tělovýchovy
  • National Natural Science Foundation of China

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