Drug abusers characteristics on the online community

Abstract

This study aims to gain insights into the basic information and behavioral characteristics of the drug abusers and provide references for drug prevention, control, and correctional strategies. First, the python development tool was used to crawl 8494 posts from 1725 users in the forum of “Dynamic Control Bar” in the Baidu Tieba. The data were cleaned and organized. Subsequently, the content of the posts in text was analyzed using a mixture of topic model, sentiment analysis, and relevance analysis. The result of the LDA indicated that the drug abusers were concerned about the living conditions of this population in their home communities, regular checkups and management by government staff, perceived social discrimination and inconvenience of living in a restrained environment, problems they encountered when consulting with each other in terms of regular medical checkups, recollection of how they came to use drugs, as well as emotions of regret. The result of the emotional analysis indicated that this population was emotionally disturbed and had more negative emotional values, but the above values were stable. Internet information dissemination is of great significance to public opinion dissemination that can indicate the real opinions and attitudes of all social strata to drug abusers, especially the discrimination, stigmatization, and labelling of drug abusers by the general public. Disseminating content to drug abusers about their problems can help them start a new life. Furthermore, the government should guide the attitudes and emotions of this population to help them start a new, more positive life.

Keywords

Drug abuse dynamic control latent dirichlet allocation sentiment analysis internet public opinion

1. Introduction

Drug abuse is defined as an addiction to drugs (e.g., opioids, cocaine, amphetamine-type stimulants, cannabinoids, hallucinogens, alcohol, and nicotine) that are capable of affecting the physiological and psychological functioning of the body and reinforce addictive tendencies [1, 2]. Drug abuse remains a worldwide public health challenge with serious negative effects on individual’s physical and psychological well-being, family functioning, and social security and economy. The World Drug Report 2020, published by the United Nations Office on Drugs and Crime (UNODC), suggested that approximately 270 million people worldwide use drugs each year, a population of 35 million become addicted, and nearly 600,000 die as a direct result of drug abuse.

The motivation and purpose of this study is to take the drug abusers in Baidu Tieba as an example to analyze the characteristics of drug abusers in Internet transmission. Through the analysis of comments, the effects of language characteristics, emotional attitudes, real psychological needs and feedback of the public on the evaluation of drug abuse behavior can be obtained, a reference can be provided for researchers to gain insights into the evolution process of topics of concern of drug abusers, and provide decision support for management departments to guide the emotional evolution of drug abusers.

Drug abusers who want to integrate into society face many problems (e.g., a lack of social support systems, deteriorating family relationships, as well as difficulties in re-employment). The above problems require professional social workers to urgently adopt professional methods and skills to intervene and help. From a higher level, the ultimate goal of social integration is to enable drug abusers to quit drugs permanently and to live a political, economic, and social life as normal people. Thus, the concept of social integration is not simply to prevent drug abusers from relapsing into drugs, but to further achieve their self-development by tapping into their inner potential and motivating them to reach a realm of autonomy, self-reliance, as well as self-discipline. Drug abusers are a special social group. On the one hand, their drug abuse behavior violates laws, regulations, and social mores. Consequently, people mostly reject them or have a discriminatory attitude to them and a poor overall impression of them, such that drug abusers are easily marginalized by mainstream society. On the other hand, they are patients and represent a vulnerable population. They encounter difficulties in many aspects of life for their drug abuse, thus making them face more problems and challenges in social integration.

People are increasingly inclined to express their opinions and emotions on social networking platforms. Moreover, social networking platforms generate considerable text data containing users’ emotional tendencies and opinions and attitudes. Social network texts pose a huge challenge to conventional text analysis tasks for their colloquial, time-sensitive and networked nature. Owing to the anonymity of the Internet, drug abusers can chat and make friends on the Internet with less psychological pressure, and even talk about the reasons for their drug abuse without any concealment. They truly display their behavioral characteristics without much fear of possible discrimination. Therefore, compared to conventional questionnaires, collecting information on drug abuse through the Internet not only saves a lot of human and material resources and obtains far more samples than can be collected by conventional questionnaires, but also results in obtaining information that is more authentic. This has a positive effect on understanding the behavioral characteristics of online drug abuse and the applied research on social integration of drug abusers. To a certain extent, it provides methods that can be implemented with reference to help this population, which is of profound significance to improving the effectiveness of anti-drug work and enriching the practical experience of this work.

2. Related work

Scholars have analyzed and explored the causes of drug abuse and have concluded that there are several reasons for this. It has been suggested that addiction is caused by the positive reinforcement of the euphoria produced by drug abuse in the addiction, i.e., the reward effect [3, 4, 5]. This has led some researchers to propose the theory of motivational sensitization [6]. Existing research has also suggested that the nature of drug abuse is a pathological memory based on drug-induced changes in synaptic plasticity [7, 8, 9, 10]. Some researchers have suggested that with the increase of drug use, the brain’s feelings of reward and goodness decrease, and the stress response becomes stronger, and the results of such studies may explain why high-social-stress events, including stigma, discrimination, unemployment, stress from distrust, strained family relationships, and negative life events (e.g., the death of a loved one or divorce) can be important causes of relapse [11, 12, 13].

Numerous intervention methods have been proposed to prevent the second relapse of drug abusers. Psychological and behavioral intervention has been confirmed as a vital means to prevent relapse. Psycho-behavioral interventions serve as an essential tool for relapse prevention. Psychological factors take on a critical significance in triggering, maintaining, or inhibiting addictive behaviors [14], and they can be employed to modify such behaviors in individuals through learning and reinforcement [15]. Existing research has suggested that addicted patients develop and internalize the above behaviors in response to risk factors for relapse through repeated skill practice, which may primarily account for the consistent efficacy of cognitive behavioral therapy (CBT) in promoting patient conduct and reducing relapse [16, 17, 18]. CBT has moderate or above-average intervention effects in increasing the conduct rates or frequency of drug use [19]. Windsor et al. [20] suggested through meta-analysis that CBT is more effective in reducing drug use in non-Latino White groups than in Black or Latino groups in a before-and-after controlled study though varying degrees of cognitive or psychiatric impairment in addicted patients affect the intervention effects of CBT [21].

The community dynamic platform for community management is created. Community drug treatment and rehabilitation are integrated into the platform [22, 23, 24]. The community treatment management system, which is based on family and friends, can demonstrate humanistic care [25, 26]. This can reduce the cost of addiction treatment and make it easier to manage and supervise. Fernandez-Montalvo et al. [27] performed a long-term evaluation of a well established addiction treatment community in Navarra (Spain). Fernandez-Montalvo also did a comparative study of those who completed the program, those who gave up midway, as well as those who relapsed into addiction. To improve treatment retention, welcoming homes (WHs), were introduced at the start of European therapeutic communities [28]. Leslie et al. [29] have analyzed discrimination against drug abusers in the workplace and social issues (e.g., the low status, unemployment, economic insecurity, social stigma, as well as social exclusion faced by women when reintegrating into society after detoxification [30]). Other researchers have discussed the policies and procedures of drug abuse treatment providers and their eligibility to offer services to clients [31].

3. Methods

Text classification and clustering have been confirmed as important text analysis techniques and core tasks in the field of text mining, which have aroused much attention from academia and industry. The task of text classification is to automatically assign pre-defined category labels in accordance with the content or subject of a given document. The text clustering task, on the other hand, divides a collection of documents into subsets based on content or topic similarity between documents, with higher similarity within the respective subset and lower similarity between subsets.

Sentiment analysis belongs to the natural language processing sub-topic, of which the essential scientific problem continues to be the semantic understanding of language and text, but with the domain specificity of emotional-emotional expression. Sentiment analysis includes a considerable number of subdivisional tasks and applications. Sentiment information extraction refers to a fine-grained task in sentiment analysis, the core objectives of which include the extraction of viewpoint objects, evaluative expressions, as well as the collocation between objects and evaluations. In viewpoint object extraction, there are usually different levels of sentiment identification and extraction regarding the viewpoint holder, the target to which the viewpoint is directed, as well as the fine-grained properties of the object. For evaluation expressions, sentiment words and sentiment expressions are usually extracted from the input content, including implicit expressions (i.e., through fact-like or other implicit descriptions) and explicit expressions (i.e., with an obvious description of the viewpoint). During the extraction of pairings between objects and evaluations, what is important is not only the identification of the opinion object or attribute and its sentiment evaluation.

Python is an open source, interpreted high-level programming language that can run on any major operating system. Python is an open source, interpreted high-level programming language that runs on any major operating system. Python’s simple syntax can save developers development time and development costs. Python has several libraries for natural language processing, but the majority of them are for processing English. The SnowNLP library is a class library written in Python specifically for processing Chinese text. In this paper, we improve and optimise it for Chinese word separation, lexical annotation, sentiment analysis, text classification and calculation of text similarity, with comprehensive functionality.

3.1 Data collection

In this study, a web crawler was designed based on Python’s “re” module [32, 33, 34] to extract the required part of the strings from web pages by fuzzy matching of strings. All the post data were crawled on the “Dynamic Control Bar” forum. The main fields crawled comprised user name, user nickname, main post name, post name, posting time, as well as post content. Data collection is performed using the requests library in python. First, find the URL Request URL of the requested page in the comments section of the site. Send a request to the server’s url object via the request.get() method and return a Response object containing the server’s resources. Next, the resultant JSON object is returned via response.json(), which converts the captured comment data into json format. In the crawled data, 1725 users participated in the discussion, with 1247 topics and 8494 posts.

3.2 Data cleaning

The post content that was irrelevant to this study (e.g., advertising information, abnormal information, and pictures and videos) was removed. Including the removal of irrelevant advertising posts and meaningless posts, 7524 posts were finally left as the data source for this study. Moreover, basic information was counted (e.g., user name and posting time) in the posting bar, and the contents of the postings were classified and summarized in chronological order.

3.3 Word separation processing

The collated text was processed by modifying typos, removing emoticons, and deleting words with no specific meaning. The content was separated into words using the cut function in the jieba library in Python, thus laying a basis for exploring subsequent studies (e.g., topic modelling and sentiment analysis). Jieba lemmatization has three modes: exact mode, full mode, and search engine mode. In this study, we aim to perform a sentiment tendency analysis of vaccine reviews. Thus, the exact mode of jieba subscripts was adopted to classify all the collected vaccine reviews.

3.4 Word frequency analysis

Word frequency analysis refers to a representative method of text content analysis. The basic principle is to identify hotspots and their trends through changes in the frequency of word occurrences. The word frequency of the respective word after word separation was counted using Couter’s function in Python. The words were sorted in descending order of frequency.

3.5 Topic model analysis

LDA (Latent Dirichlet Allocation) was proposed by Blei et al. in 2003 [35] to infer the topic distribution of a document by analyzing the different probabilities of occurrence of the same word in different topic contexts. There is no order or sequential relationship between words. A document can contain multiple topics, and each word in the document was generated by one of the topics. Thus, by analyzing some documents to extract their topic distribution, topic clustering or text classification can be performed based on the topic distribution [36, 37]. The process of LDA model analysis is presented as follows: the number of topics is determined $\to$ topic words are extracted $\to$ classification topics are established $\to$ probability statistics and ranking. Inspired by this model, this study mines potential themes corresponding to items from item-type relationships with the help of the LDA theme model, clusters items by themes, and constructs an item-topic relationship matrix to indicate data laws more scientifically than the literature has. In this study, the LDA library in Python tools were employed, and the parameters alpha $=$ 1.25, beta $=$ 0.1, and K $=$ 5 were set to analyze the text for the topic model. The key codes are as follows: ⟀ dset $=$ readtrnfile() // read file ⟁ model $=$ Model(dset) // Parameter settings ⟂ model.init_est() // Perform LDA calculations ⟃ model.estimate() // LDA Outcome Assessment.

3.6 Sentiment analysis

Text sentiment analysis is also known as opinion mining and disposition analysis. It is the process of analyzing, processing, generalizing, and reasoning about subjective texts with emotional overtones [38]. In this study, SnowNLP in Python was adopted to perform sentiment analysis on the text of each post. The sentiment analysis took the value expressing the probability that the sentence represents a positive sentiment, and its value range was (0, 1). The closer the sentiment value to 1, i.e., the more positive the sentiment will be expressed; the closer the sentiment value to 0, the more negative the sentiment will be. The key codes are as follows: ⟀ from snownlp import SnowNLP ⟁ Calculating sentiment values ⟂ return s.sentiments // Return sentiment value.

4. Results

4.1 Data source

Owing to the small number of official websites on drug abuse in China, the lack of authority and effect, and the lack of interactive sections, it was impossible to conduct an analysis. Accordingly, Baidu’s “Dynamic Control Bar,” which has a high degree of attention, wide effect, and frequent interaction, was selected as the research object in this study. The Baidu’s “Dynamic Control Bar,” created in 2017, has quickly attracted numerous drug abusers for its distinctive public welfare nature and the optimistic atmosphere of the bar. Currently, there have been nearly 2,023 registered members in the bar, and most of the information exchanged between members in the bar is the transmission of drug abuse information. Accordingly, the “dynamic control bar” refers to a suitable object to study the social support of drug abusers in cyberspace. This study collected, organized, and analyzed a wide variety of data points from the “dynamic control bar” to gain more insights into the information characteristics of drug abusers’ concerns. All the posts were crawled on the “Dynamic Control” forum. The main fields crawled comprised user name, user nickname, main post name, post name, posting time, as well as post content. In the crawled data, there were 1725 users participating in the discussion, with 1247 topics and 8494 posts. The data among them were cleaned, including removing irrelevant advertising posts and meaningless posts and selecting posts between the establishment of this bar in 2017 and June 11, 2021. Lastly, 7,524 posts were left as the data source for this study.

4.2 Trend analysis of the number of posts made

The number of posts between January 1, 2017 and June 11, 2021 was calculated by date. As depicted in Fig. 1, before April 2019, the number of posts was low since the “dynamic control bar” was established and did not attract the attention of netizens to dynamic control. Starting in 2019, with the further improvement of the national control policy on drug users and the increase of drug users, there was a wider range of public concern and discussion.

Figure 1.

Number of posts published daily.

As depicted in Fig. 2, the number of postings in a week was more on weekdays than on weekends, and the number of postings was the highest on Thursdays. As depicted in Fig. 3, the posting volume was the lowest from 3:00 a.m. to 7:00 a.m. in a day, since this time is mainly non-working time and Internet users have a lot of time to post online during their rest time. The posting volume mostly ranged from 16:00 p.m. to 18:00 p.m., followed by the posting volume from 21:00 p.m. to 24:00 p.m. as well as from 11:00 p.m. to 13:00 p.m. The main reason is that the above times represent free time outside work when Internet users have time for online communication.

Figure 2.

Number of posts published in a week and in a day.

4.3 Hottest posts

Table 1 lists the top five posts with the most replies by response statistics. As depicted in the table, the posts with high attention were concentrated in 2021 and 2019, and the post topics involved the discussion of developing an exchange QQ group (2021-01-19) to facilitate direct exchange and discussion in the group. This result suggests that users require a faster and more convenient way to exchange information, and controlled drug users are more concerned about privacy and have a greater sense of security and belonging in the QQ. Moreover, controlled drug users are more concerned about privacy and gain a greater sense of security and belonging when communicating in QQ groups. Furthermore, there were some classic and routine questions for people under drug control, including “the problem of swiping ID cards with the police pass” (2019-07-17), which is a question of what IDs should be prepared when being checked, as well as “can’t change my card, expiration date” (2021-04-20), which is the problem of how to operate when the driver’s license is due to be replaced by a controlled drug user. “Today the police station notified to let go home, saying what hair test, have you encountered” (2019-06-18) represents some of the doubts of being checked, or their bodies being controlled. Besides some of the problems of the above drug abusers, there were also some posts from netizens who helped them, including “Guangzhou criminal defense, professional answers to bar users’ questions, focus on criminal defense, and fine in drug defense” (2021-05-30), which is a lawyer volunteering to answer legal questions for drug abusers in a controlled context.

Table 1
Lists the TOP 5 hot subjects

Post subject	Visu-shrink	Number of replies	Posting time	Bayes-shrink
Dynamic control exchange group	28.76	41	2021-01-19	33.32
About the police pass swipe ID card problem has been tried today	26.46	30	2019-07-17	30.17
Guangzhou criminal defense, professional answers to the bar’s	25.14	30	2021-05-30	28.48
questions, focus on criminal defense, fine in drug defense
Cannot change the certificate, the expiration date	24.81	30	2021-04-20	30.86
Today the police station notice to go home, said what hair testing,	22.81	30	2019-06-18	27.13
everyone has encountered?

4.4 User statistics

Figure 3 presents the user posting statistics. The number of posts of individual users was concentrated between 1 and 10, and the largest number of posts reached 1, thus indicating that most users still mainly read and obtained information, and active sharing of information was concentrated in a small number of users. The highest posting users posted 111 times, and the topics and contents of public postings were primarily correlated with how to cope with control and psychological reassurance.

Figure 3.

Statistics on the number of posts by individual users.

4.5 Text analysis

After the parameters and text analysis of the posting content were set, it was found that the posting content can be classified into the five topics as follows.

As depicted in Table 2, the five themes are presented as follows: the living conditions of the controlled persons in the home community; the regular inspection and management of the controlled persons by the government staff; the inconvenience of being discriminated against in the society and having their lives restrained; consulting with each other about the problems they encountered during the regular medical checkups; the controlled persons’ recollections of how they went down the path of drug abuse and how they felt regretful after being caught and controlled by the police. There were also some recollections of how they came to take drugs and how they regretted being caught and controlled by the police. The above topics covered all aspects of the drug abusers’ lives in the control process, thus indicating that the drug abusers were particularly concerned about their lives in control, regretted their drug use, and were interested in discussing their new lives after rehabilitation.

Table 2
Text analysis by topic model divided into 5 topics

Serial number	Topics	High frequency words	Posting time	Bayes-shrink
Topic 1	Community control of drug rehabilitation work	Community, drug rehabilitation, said, three years, year, police station, urine test, work, do, month, control	2021-01-19	33.32
Topic 2	Dispensaries regularly check on drug addicts	Check, dynamic, police station, year, face, drug, ID, social, month, situation	2019-07-17	30.17
Topic 3	Drug addicts are controlled and their lives are affected	Exist or not, drug, ID, driver’s license, detention, personnel, high, dynamic, system, work, catch, play	2021-05-30	28.48
Topic 4	Regular medical checkups for drug addicts	Urine test, drug rehabilitation, police station, questioning, drug use, testing, social, first, hair test, situation, hair, notice	2021-04-20	30.86
Topic 5	Drug addicts recall the reason for being controlled	Social, drug rehabilitation, want, high, first, detention, drug use, ID, record, social rehabilitation, rooming, catch, situation	2019-06-18	27.13

Figure 4.

Sentiment values changing within a week and within a day.

4.6 Sentiment analysis

Positive and negative sentiment analysis of post text by day of the week and time of the day was conducted, and the mean function was adopted to process the sentiment analysis result values. As depicted in Fig. 4, most of the values ranged from 0.3 to 0.4, indicating that the sentiment values of dynamic control users posting in the posting bar were more on the negative side. Notably, Thursday had the lowest value, mainly because Thursday is in the middle of the working week, and work pressure causes emotional anxiety, thus affecting negative and low emotions. The number of posts on that day was low, and the content of the posts had low emotional value, such that the average emotional value was low. Within the day, 6 am exhibited the highest value of emotion, since the body is full of energy and vitality early in the morning. Furthermore, the mind is clear and full of positive emotions, resulting in a high emotion value at this time of the day. Except for the above times, the emotion values of other times were stable and did not fluctuate significantly, thus suggesting that the emotion of the controlled people did not fluctuate much.

5. Discussion

In this study, drug abusers were taken as the research object. Mathematical statistics and time series analysis were conducted on the data in Baidu postings, and the factors for the online information dissemination of drug abusers were analyzed in terms of posting hotness, user analysis, topic model, as well as sentiment analysis. The results of the study indicated that: (1) The diversity, simplicity, and speed of online networks’ communication methods made the public willing to obtain and share information online and express their opinions and emotions about events. (2) The information relating to drug abusers in postings was more significantly correlated with the development of national policies, and the focus and hotness of drug abuser discussions changed with the dynamic control of drug abusers in China. (3) Drug abusers’ discussions regarding their controlled lives involved several aspects (e.g., community control of drug treatment efforts, how drug abusers are controlled and have regular medical checkups, how their lives are affected and discriminated against in society, as well as how drug abusers recall the reasons for being controlled). This indicates that drug abusers are concerned with the harmful effects on their personal bodies and lives since initiating the drug abuse, while regretting their drug abuse and coming to realize that drug abuse is a wrong behavior. (4) There were many positive talks though the drug abusers’ emotions were relatively stable and negative overall during the dynamic control. It is therefore revealed that drug abusers recognize drug abuse as a negative thing, whereas they are also filled with positive emotions.

6. Conclusions

The research results suggest that the government’s public administration copes with the regulation and guidance of drug abusers as follows: (1) First, online information dissemination is of great significance to public opinion dissemination that can indicate the real opinions and attitudes of all social strata to drug abusers, especially the discrimination, stigmatization, and labeling of drug abusers by the general public. The above attitudes cause a crisis of trust in drug abusers, who are difficult to integrate into society and should be given high priority by the relevant media and government departments. (2) From the perspective of the content of communication, the harm of drug abuse should be vigorously publicized, such that the public can understand the harm caused by drug abuse to individuals, families, and societies, and avoid making the mistake of drug abuse. At the same time, the content of drug abusers should be disseminated to help them start a new life after they have been led astray. (3) From the perspective of the communication subject, we should pay more attention to and guide the attitudes and emotions of drug abusers, not only to solve the difficulties and problems they encounter in their actual lives, but also to soothe their emotions, channel their negative emotions, and encourage drug abusers to start a new life positively. (4) Starting from the perspective of dynamic control, we should adopt a model of combining controls by multiple management entities and improve the professionalism of anti-drug social workers. The dynamic control of drug abusers is systematic work, and the control of drug abusers involves multiple departments, which need to be linked seamlessly to prevent the problem of missing and missing control of drug abusers. The government should clarify the responsibilities of various departments and make them work together to promote the return of drug abusers in the community. Besides, the government is required to optimize the mechanism of community drug treatment and develop a sound “triple social linkage” mechanism linking the community, community organizations, and professional societies. Moreover, it is imperative for the government to allow professional social workers to give full play to their unique role in the community drug treatment work. Furthermore, the government should vigorously develop anti-drug social organizations and teams and adapt to the requirements of work development in accordance with quantity and quality.

Internet information dissemination is of great significance to public opinion dissemination that is capable of indicating the real opinions and attitudes of all social strata to drug abusers, especially the discrimination, stigmatization, and labeling of drug abusers by the general public. The aim of this study is to understand the basic information and behavioral characteristics of the drug abusers and provide a reference for drug prevention, control, as well as correctional strategies. Disseminating content to drug abusers about understanding their problem can help them start a new life. Furthermore, they should guide the attitudes and emotions of this population to help them start a new, more positive life.

Footnotes

Acknowledgments

We are grateful for the support of XinGang Social Work Institute. We also appreciate all Participants who contributed to the data collection and analysis in this study.

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Drug abusers characteristics on the online community

Abstract

Keywords

1. Introduction

2. Related work

3. Methods

3.1 Data collection

3.2 Data cleaning

3.3 Word separation processing

3.4 Word frequency analysis

3.5 Topic model analysis

3.6 Sentiment analysis

4. Results

4.1 Data source

4.2 Trend analysis of the number of posts made

Table 1 Lists the TOP 5 hot subjects

Table 2 Text analysis by topic model divided into 5 topics

5. Discussion

6. Conclusions

Footnotes

Acknowledgments

References

Table 1
Lists the TOP 5 hot subjects

Table 2
Text analysis by topic model divided into 5 topics