Abstract
With the popularization of social networks, the abundance of unstructured data regarding environmental complaints is rapidly increasing. This study established a text mining framework for Chinese civil environmental complaints and analyzed the characteristics of environmental complaints, including keywords, sentiment, and semantic networks, with two–year environmental complaints records in Guangzhou city, China. The results show that the keywords of environmental complaints can be effectively extracted, providing an accurate entry point for solving environmental problems; light pollution complaints are the most negative, and electromagnetic radiation complaints have the most fluctuating emotions, which may be due to the diversity of citizens’ perceptions of pollution; the nodes of the semantic network reveal that citizens pay the most attention to pollution sources but the least attention to stakeholders; the edges of the semantic network shows that pollution sources and pollution receptors show the most concerning relationship, and the pollution receptors’ relationships with pollution behaviors, sensory features, stakeholders, and individual health are also highlighted by citizens. Thus, environmental pollution management should not only strengthen the control of pollution sources but also pay attention to these characteristics. This study provides an efficient technical method for unstructured data analysis, which may be helpful for precise and smart environmental management.
Highlights
Environmental quality has become a critical factor for improving urban sustainability [1]
Light pollution complaints are the most negative, and EM radiation complaints have the most fluctuating emotions, which may be caused by differences in citizen perception of EM radiation
(3) The semantic network nodes of the six types of environmental complaints reveal that the public pays the most attention to the pollution sources when complaining but the least attention to stakeholders, which may reduce the efficiency of environmental managers in handling complaints
Summary
Environmental quality has become a critical factor for improving urban sustainability [1]. Text mining is the process of extracting previously unknown, understandable, potential, and practical patterns or knowledge from the collection of text data [2] It has been actively used in various fields, including biomedical, medicine [15], risk management [16], policy, crime [17], market such as multilingual recommendation system [18], education, and informatic fields. Some scholars have carried out research on complaint text These studies focused on the following aspects: semantic network analysis and keyword analysis of citizen complaints [19]; use of text mining to determine citizens’ policy needs for safety and disaster management [20]; and the utilization of text mining to identify and evaluate the indicators of cultural ecosystem services [21]. TThhee ttwwoo––yyeeaarr ddaattaa ((ffrroomm 11 MMaarrcchh 22001188 ttoo3311MMaarrcchh22002200))wweerreerreettrriieevveeddffrroommtthhee wweebbssiittee of tohfe GtuhaengzGhouuanMgzuhnoiucipalMEucnoliocigpiaclal EEncvoirloognimcaelnt BEunrveiaruon(mhtetpn:t//sBthujrj.egazu. gdgm(ccohooaooritvvtdsnnte.sespttc,iaernn:wncni//gn/otmsi,zmttgththgehelpnojmeojm.lvtggad/erirziasetrna.sstnsgpteijpbmonh,IozvgDciecnx.onc,g/smintndee,/,oprfizaoseagltctsarnlrcrmmpiaidencops/attrntshtseIeaisiDjosdcebnpn,,zdioo,adxnnnan/afi,nsosdd3teardrd1mcridrucecMeaatesnspttsaiaisesdoon,re(nencddfiThns,araetoamb2idnfind0ldesde2a,3rd0t1e1uet))soc..nMs(opW TT,imdiafahceierbprencomollhetcfabisoif1ct2n,imao)e0tt.imdo2npcWp0oelpc)aidneo.cliatnmT5oeoit6hnnbfps7etttcl,ad2awocicaimnvonaoteamatsmpdlsicelpedpaox5tlilnacs6rnalie7titcunecn2,odtnoctsnvetroctdaddmwaols.aiinpandtwtasleatrsihneeetinhxcetts,--t cluded
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