TikTok is among the most popular social media, with over a billion users worldwide. While the app gives a platform for content creators to utilize original music in their video posts, the use of unlicensed music can lead to copyright infringements. This study examines the overall perception of copyright regulations among TikTok users by analyzing a sample of Twitter posts discussing this issue among users presumed to use both apps actively. The quantitative and qualitative content analysis methods will be used to understand the critical narratives in users’ perceptions of copyright. The research examines 500 tweets that closely relate to the issue using machine learning algorithms and logDice to find a meaningful network of words in the aggregated text. The analysis substantially confirmed the research hypotheses, including the general satisfaction with TikTok copyright rules and the extensive overlap between the concerns about the app’s ties to China’s government and intellectual property regulations.
TikTok has become a viral platform for creating short videos, gaining over 1 billion users. Recently, it has surpassed other popular social media, including Facebook and Snapchat (Moreno, 2021). The app provides a platform for users to publish short videos with background music, allowing millions of people to create videos, often including dancing to popular songs. Unlike other widely used social media, TikTok was developed in China, an authoritarian state with strict censorship and media control. In contrast to the US-developed Instagram, Facebook, and Twitter, TikTok is the creation of IT specialists heavily connected to the Communist Party of China (Knowles, 2019). Within this context, this research focuses on a narrower aspect – how individuals talk about the intellectual property rules in TikTok.
Statement of the Problem
There is a problem that many users use unlicensed music tracks in their TikTok videos, which moderation does not block and delete. Music labels do not want an uncontrolled distribution of their product, wanting to have guarantees that their artists’ music is used legally (Michalko, 2020). Nevertheless, the TikTok administration often ignores the use of pirated content, as artists receive a massive boost in recognition concurring with the correspondingly increasing popularity of the platform. Although the media extensively discusses TikTok’s relations with music companies on legal issues, the users’ use of language online on intellectual property lacks coverage (Chalmers, 2020a; Chalmers, 2020b; Gleason, 2020). As such, this study aims to create a clearer understanding of TikTok’s IP problems and how people talk about these issues in social media, primarily Twitter.
Objectives of the Study
This paper addresses the current research problem of insufficient awareness of TikTok users’ discussions and conversations about the application’s intellectual property policies. This information will inform the general community about regular TikTok users’ voiced opinions of intellectual property, the potential repercussions of utilizing unlicensed music, and their desire to keep relaxed restrictions. This study aims to compensate for the lack of coverage in the media and within the general community of how everyday TikTok users talk about the platform’s copyright regulations and their implications.
Significance of the Study
Gaining a clearer understanding of the customer “demand-side” may help TikTok tailor regulations to meet the needs of all stakeholders. The research method involves data mining posts and tweets from TikTok and Twitter discussing rules of intellectual property in TikTok. Identifying the primary narratives and keywords used in these discussions will help form potentially generalizable implications regarding the user talking points of TikTok’s intellectual property regulations. These implications could potentially be extrapolated onto a wider TikTok population, although a larger sample size would likely lead to more accurate results.
Limitations of the Study
The apparent study limitation is the relatively narrow sample size due to the exclusiveness of the collected sample group during the data mining stage, which might undermine the validity of the research findings. The study acknowledges that there is a risk the sample may not be representative of a broader population of TikTok users and contain a disproportional quantity of either positively or negatively skewed messages. Although irrelevant words and phrases are deleted from the sample, the typicality of the collected words and phrases may lead to insufficient variability that can compromise the accuracy of research conclusions. Lastly, the presence of slang, abbreviations, hashtags, and lexical, grammatical, and logical errors in the collected text data may further complicate the analysis.
Review of Related Literature
Moreover, the items discussed above can result in General Data Protection Regulation or GDPR regulation violations. One should be aware that “the GDPR applies to you even if you’re not in the EU … the fines for violating the GDPR are very high” (GDPR, 2022, para. 2). GDPR is primarily concerned with personal data, data processing, data subject, data processor, and data controller (GDPR, 2022). In other words, an entity processing data, such as TikTok, is responsible for demonstrating compliance with the regulations. Data processing and storage must be secure, confidential, and appropriate. In addition, data minimization is vital, where an entity must not collect any additional data more than what is needed for specific reasons. Lastly, the processing of data must be transparent and lawful to all parties, especially data subjects. Any misuse or mismanagement of users’ data is a direct violation of GDPR principles.
Despite the general public’s discussions on the app’s potential ties to the authoritarian state, TikTok’s popularity is continually rising. Current projections suggest a 22% annual growth rate in the number of TikTok users in the US (Connell, 2022). Two explanations present themselves for this contradictory trend. On the one hand, TikTok denies these accusations, stating that its data servers, processing sensitive information about American citizens, are in Virginia and backed up in Singapore (Sanger, 2020). Nonetheless, this does not confirm TikTok’s autonomy from the Chinese government.
On the other hand, users may generally be unconcerned about the risk of compromised data privacy by a foreign government and continue enjoying the app’s services without worrying about possible data insecurity. This uncertainty about users’ conversations facilitates the research interest. In the case of GDPR policies, the data controller, such an intellectual property owner, must be protected by the data processors (TikTok) (GDPR, 2022). This is especially relevant for data residency, which is concerned with the geographic location of data. The laws on data residency mandate that organizations need to keep and securely store data in the country the data coming from (GDPR, 2022). In other words, TikTok needs to ensure that data collected from a UK citizen needs to be stored in the UK in compliance with local regulations.
The research question posed in the study is: How do TikTok users observe and talk about the platform’s application of intellectual property rules? This question sets concrete boundaries for the research results. The research methodology involves a multi-step data gathering and analysis model. Firstly, the blocks of text where users’ opinion on intellectual property rules is expressed are collected. With a sufficient sample size, an analysis in RStudio is used to examine the typicality of word use concerning user expressions on the TikTok intellectual property regulations.
One reason for the users’ opinions to vary and for this study to be interesting is the platform’s usage of blockchain technologies. TikTok attempts to partner with blockchain companies to track intellectual property infringements (Hissong, 2021). The media platform is set to utilize this technology to prevent the distribution of unlicensed content while generating profit for artists, which is somewhat an ambiguous method. Therefore, these enhanced restrictions raise concerns about content availability, which might negatively affect the TikTok user experience.
The ambiguity around enforcing intellectual property rules may create a conflicting scenario for artists. On the one hand, TikTok’s massive audience helps boost popularity, with a recent example being Lil Nas X gaining his initial massive success with his song becoming viral on TikTok (Fowlkes, 2019). However, expanding a fanbase may come at the cost of allowing users, unknowingly and knowingly, to continue violating music copyright. Thus, artists may find themselves in a tight spot where enacting copyright restrictions on their recordings might subsequently curtail the spread of their content and their popularity growth.
As for user behavior, it is hard to understand user’s use of language online due to the limited literature on users’ discussions of intellectual property rules for TikTok specifically. Certain studies examine TikTok user behavior from the perspective of determining reasons for prolonged time-spending on the app. For instance, Montag et al. (2021) propose two explanations for prolonged use. First, the gratification theory suggests that social media helps fulfill users’ social needs. Second, user engagement is sustained through AI-driven psychological microtargeting techniques. While TikTok generally serves entertainment purposes, it also actively encourages TikTok content creators to use the platform for self-realization.
Lastly, TikTok’s continued negligence of copyright could be explained by the “user-centric” theory. It suggests that focusing on sustaining continuous user engagement by addressing direct user needs instead of third-party needs is more financially beneficial in the long term (Yu, 2019). As such, TikTok’s massive success is largely indicative of its user-centered approach. Based on this assumption, the possible expectation is that public opinion will be relatively mild about copyright issues. This expectation also stems from the highly specific descriptions of copyright restrictions in the Twitter posts sample that would otherwise not have been created by passive TikTok users who would rarely encounter these restrictions. In other words, the sample primarily indicates that these Twitter users in the collected sample are also most likely regular TikTok users and content creators. The latter statement means that these users are likely to be affected by copyright infringement in one or more ways.
Operational Definition of Terms
This study defines users as accounts on both social media, Twitter and TikTok, engaging in TikTok copyright discussion. In this study, the discussion on senses and psychological consequences will be omitted because this research deals with social science research (Ruane, 2016). At the same time, language is expressed through words and phrases, which can provide a general picture on how the public discusses and talks about the IP issues on TikTok online.
Guided by the aforementioned data-focused theoretical frameworks, this study presents hypotheses that can be assessed through data analysis. While expected to be primarily descriptive and introductory, this study acknowledges the difficulty of full-fledged hypotheses testing on a larger sample size due to the current lack of understanding of users’ use of language online about intellectual property regulations. Thus, these assumptions try to highlight the expected expressions and ideas from the results of the empirical study:
- H1: The users of TikTok will be overall satisfied with the intellectual property regulations.
- H2: Being concerned with TikTok’s ties with the Chinese government, users will overly link intellectual property regulations with Chinese influence.
This study uses quantitative and qualitative methods to form knowledge of users’ use of language online by analyzing the keyword data. The qualitative content analysis method is helpful because it allows researchers to understand key patterns in how the users talk about these issues. The quantitative method involves searching for the most frequent narratives and collocations in the sample. Quantitative methods are practical in sorting out the most relevant user expressions in a relatively large sample size.
Scope of the Study
The scope of the study is Twitter, which is the most appropriate source because TikTok and Instagram do not have efficient services for data collection. For example, in TikTok, the main text is located in the video, while the written description for this video post usually contains only hashtags for content promotion. As for Instagram, there are limited capacities for sorting posts and finding the most relevant among them. Twitter, the search engine has broad applicability where a researcher can set a time frame and keywords.
Respondents of the Study
It is impossible to identify the overall makeup of respondents of the study because the vital characteristic of Twitter is that people prefer having anonymous accounts for posting without personal images. Therefore, the research limitation is a blind zone between the researcher and the respondents. Nevertheless, there is a strong possibility that most people in the sample are active users of TikTok because they write extensively specific opinions about the peculiarities of TikTok intellectual property regulations. In addition, the latter can additionally include affected users, whose intellectual properties were not protected as needed in accordance with a multitude of regulations, including GDPR. These highly detailed descriptions that otherwise would possibly not have been written by irregular TikTok users who would rarely stumble upon copyright restrictions indicate that these Twitter users are also almost certainly active TikTok users.
The sampling procedure involves sorting out an accurate sample of posts by using specific topic-related keywords. The data collection engages searching for tweets using phrases such as “Tik Tok/TikTok copyright rules,” “Tik Tok/TikTok intellectual property,” “intellectual property awareness,” “my audio was stolen,” and “I own the original audio.” These specific keywords make it unlikely to include irrelevant tweets, as combining “TikTok” and “intellectual property” or “copyright” phrases in a single expression increases the chance of its topicality.
Data Gathering Procedure
The data was collected using an application called “Data Miner.” It works as an add-on to Google Chrome with built-in algorithms for efficiently managing relatively large data sets. This application already included instructions for data mining on Twitter, allowing to reduce the time to collect enough observations substantially. Then, this information is analyzed in two ways: descriptive and analytical. In the first instance, the collected sample of expressions on intellectual property is critically examined. In the second instance, the quantitative methods using logDice and networks of words and keywords in phrases help produce possible insights on user awareness of empirical data. Together, these methods show the underlying patterns in how the language is used with their corresponding commonalities.
The sample contains 500 tweets collected within the 2019-2021 timeframe. The mined tweets were then added to the.csv dataset and uploaded to RStudio for further operation with texts. RStudio is a data analysis application commonly used by social scientists. Additionally, the text data will undergo lemmatization, the process of classifying inflected forms of a word under a single unit in the infinitive form. For instance, during lemmatization, the words and phrasal keywords “songs” and “song” or “stealing” and “stole” will be grouped as a single term. This is followed by tokenization, which is the process of dividing sentences into words and keywords from phrases based on whitespaces and punctuations to make the text suitable for processing by machine learning algorithms. The phrases used during data collection include “intellectual property,” “copyright rules,” and “property infringement,” among others. The phrases used included “intellectual property awareness,” “my audio was stolen,” and “I own the original audio.” The algorithms analyzed the frequencies of these phrases in the data sample. Furthermore, the multi-level relationship between words and phrases was analyzed in searching for meaningful networks of keywords using logDice.
Following the implementation of quantitative techniques is the qualitative method. Understanding the characteristic narratives in users’ tweets is beneficial in manually examining these expressions. A close reading of tweets will help understand what people most likely wanted to express. In some sense, such a procedure is similar to content analysis. However, such manual work is not guided by the principles of qualitative studies and just presents the simplified version of operating with text and interpreting it.
Firstly, the aim was to determine the frequency of word use among tweets. This study uses both single words and keywords from collocations or phrases. The results are presented in Tables 1-2. Interestingly, Table 1 includes the word “China,” which refers to the connection between the Chinese authoritarian government and TikTok. In this table, it is hard to identify the direction of users’ awareness: whether it is positive or negative. As for Table 2, the collocations “property infringement” and “property theft” present some negative connotations for the term. The phrases used included “intellectual property awareness,” “my audio was stolen,” and “I own the original audio.” It may indicate that users fully realize that the illicit use of music violates copyright and is inappropriate by intellectual property standards. It seems that the collocation “bad cover” relates to the dissatisfaction of some users with the way how someone remade a song.
The socio-demographic profile of respondents consists mostly of specific groups. It should be noted that individuals most likely inclined to discuss and express their voices on TikTok’s intellectual property issues are original content creators, music producers, and legal professionals (Montag et al., 2021). The general public is less likely to be aware of or interested in IP violations on the platform (Montag et al., 2021). Since IP laws are stronger in Western nations, the majority of respondents are from Europe and North America. In addition, these individuals come from high socioeconomic status groups because the biggest losses are incurred by the top content creators, whose IP rights are violated.
Network of Words and Keywords from Phrases
The network of words and keywords from phrases helps identify the “hierarchy” between keywords by predicting which words and phrases are most likely to appear after certain words. As Figure 1 indicates, there are no substantially meaningful networks that merit comment. The only peculiarity is the already discussed presence of the keywords “infringement,” “theft,” and “stealing.” In addition, the phrases used included “intellectual property awareness,” “my audio was stolen,” and “I own the original audio.” The qualitative research of the sample below will help understand the overall nature of this characteristic word use.
Network of Words and Phrasal Keywords based on LogDice
Complex multi-level relationships in the co-occurrence of individual words and phrasal keywords can be visualized and analyzed as a network (Figure 2). It is important to note here that in the case of TikTok, all keywords are concentrated around one center and the word “TikTok.” While one could expect to see other topics forming their unique networks of keywords within these documents, this was not observed in this study. Inspecting Figure 2, one can realize the politicization of intellectual property regulations. The keywords like “Chinese,” “CCP” (Chinese Communist Party), “communists,” and “China’s” indicates a politically contextualized outlook with which users perceive TikTok’s actions. Thus, it appears unfeasible to detach TikTok’s operations from the authoritarian regime in the current discourse.
Qualitative Look on the Sample
Firstly, it is helpful to explore how the politicization of intellectual property regulations in TikTok occurs. While the lack of transparency on TikTok’s algorithms raises concerns of data misappropriation by the Chinese government, these algorithms are what allowed the app to resonate among users worldwide in the first place. This tension is further exacerbated by the speculations of a possible TikTok acquisition by American investors and China’s refusal to export the app’s algorithms (Tamny, 2020; Huang & Levy, 2020). Interestingly, this discussion also claims that promoting videos through these algorithms may be an ideological tool China does not want to give up. Lastly, concerning the Chinese influence, Donald Trump supporters appear to have a highly negative stance toward TikTok and China (Deccan Chronicle, 2020). For instance, the data sample included a tweet saying, “American companies face plenty of barriers in China… intellectual property theft remains a big problem…ban TikTok, period !!”. Here TikTok is rhetorically attached to the Communist Party’s sensitive assets, meaning there is a direct association between the Chinese government and TikTok copyright regulations in the user’s awareness.
As for general user complaints, a common concern is that creator accounts may be blocked randomly without an apparent reason. Users complain about blocking due to “copyright infringement” and note that they did not violate such rules. At the same time, not a single comment was found that would indicate the rigidity of intellectual property regulation. A lot of people say that the rules in TikTok are considerably loose, unlike, for example, on YouTube. This positive and neutral awareness towards copyright rules can be explained by the fact that many users who write in English live in the US, where the principles of private property are of paramount importance.
Conclusion and Recommendations
In sum, the given paper discusses users’ use of language online on intellectual property regulations in TikTok using tweets of users presumed to be both active TikTok and Twitter users. The literature review noted that the links of TikTok with the Chinese government determine the critical narratives of discussion on intellectual property. As for copyright rules in TikTok, they restrict the distribution of unlicensed music if there is no agreement with music labels.
During the study, two hypotheses were stated: one about overall satisfaction and the second about the prevalence of connections with the Chinese government. The quantitative analysis of 500 tweets, including calculating word frequencies and logDice indicated the prevalent narrative of the TikTok-China connection in user awareness. Users’ use of language online about intellectual property rules were not negatively- or positively skewed, suggesting a substantially neutral stance on copyright rules. Thus, two hypotheses may be regarded as partly confirmed.
This study attempted to determine user awareness of TikTok copyright regulations using up-to-date text analysis methods. Concerning implications for future research, the general satisfaction with intellectual property rules among the English-speaking audience is worth noting. To retain its popularity, TikTok should continue to distance itself from its association with the oppressive Chinese regime, as it creates a negative public discussion. Future research warrants data analysis of expressions in other non-English languages to identify common cross-linguistic narratives. It should be noted that another main problem is the lack of clear strategic objectives and a single developed long-term program for the protection of rights. The development of such a program should be based on legislative regulation, have scientific justification and organizational support, and be supported by judicial practice. It should be taken into account that the global and rapid development of technologies will make it possible to develop a program in the shortest possible time while maintaining a balance of national and departmental interests of copyright holders, taking into account globalization and other trends currently taking place in the modern world.
The problem of copyright infringement will always be relevant in a world where data dissemination technologies are highly developed. One of its solutions is to toughen penalties, for example, by increasing the number of fines and compensations up to several times the profit lost by the owners. The amendments will not be able to eliminate this problem, and yet such cases should be reduced and become isolated. Another possible solution would be to prosecute offenders such as TikTok. Such companies may be required to control the data transmitted by users in accordance with the laws of the countries from which the data is taken.
The next action on the part of nations might be to reduce the term of copyright in order to equalize the rights of copyright holders and those wishing to use their intellectual property. It appears that the time frame currently set is excessively long. The exclusive property right of the author of the work should be reduced, and after its expiration, it should be transferred to life-long, limited possession while allowing others to legally use this product after the expiration of the above period. It is the combination of these factors that will help to prove that your rights have been violated and protect them. One of the ways to qualify the types of protection is the way of a settlement agreement and litigation. Each copyright holder, first of all, wants to resolve such disputes quickly and peacefully, as well as stop the illegal use of intellectual property as soon as possible so as not to incur even greater losses.
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