“We are no scapegoat.”: analyzing community response to legislative targeting in U.S. Texas State Senate bill 147 discourse on Twitter (X)

2.1 Actor-network theory (ANT)

Actor-network theory (ANT), introduced by Michel Callon, focuses on understanding how social forces and different actors influence the development of technological artefacts, systems and networks (see Callon 1999; Latour 1996). ANT posits that social networks consist of a heterogeneous mix of human and non-human actors (Callon 1999). ANT emphasizes that non-human actors are just as important as human actors in shaping social reality. Latour further argued that without the participation of non-human actors, it would be difficult to understand the integration of society as a whole (1996). Walsham (1997) also noted that ANT explores the formation and coextensive networks comprising both human and non-human elements. According to ANT, actors within these networks can include a range of entities, such as individuals, organizations, objects, laws, software, computer and communications hardware, and other non-human entities.

One of the important elements of ANT is the concept of agency, which refers to the actors’ ability to shape others’ actions in the network (Sayes 2014). ANT posits a position of symmetry, implying that non-human actors can also have agency, so as human actors (Dwiartama and Rosin 2014; Sayes 2014). The influence is mutual – human and non-human actors are intertwined in the social networks that non-human actors such as objects and technologies can influence human behaviors, whereas human actors can shape the behaviors of non-human actors (Kolli and Khajeheian 2020; Vicsek et al. 2016). Another key concept in ANT is the idea of translation (Walsham 1997). This process involves different actors within a network constructing a shared understanding through various forms of communication, such as language, symbols, gestures, and physical interactions (Best and Walters 2013; Vicsek et al. 2016; Walsham 1997).

Latour (2005) introduced four research areas appropriate for applying ANT. The first area focuses on the field of innovation, while the second discusses the situations that are user-unfriendly. The third area concerns incidents such as accidents, breakdowns, and strikes; in which, ANT can unfold the relationships that become apparent when normal operations are disrupted (Vicsek et al. 2016). The final area involves the historical analysis of technologies and technological systems, where ANT helps to trace their development and influence.

In addition to the four research areas previously mentioned, recent developments in ANT include studies on visualizing connections between different entities in the networked space (see Vicsek et al. 2016). This approach renders ANT a useful theoretical framework in studying social movement by focusing on interactions between human and non-human actors within social networks. For example, Brunner and Partlow-Lefevre (2020) applied the concept of “wild public networks” to analyze the connections among activists, media technologies, and other actors in the #MeToo movement. Similarly, Poell and colleagues (2014) utilized ANT to explore how textual contents on Chinese Weibo was shaped by technological features, user cultures, censorship practices, and government interventions. Furthermore, Fang (2023) employed ANT in his study of 2019 Hong Kong umbrella protests, identifying key actors in the network and examining their interactions to achieve collective objectives. All of these examples highlighted the value of ANT in clarifying the complex dynamics within social movement.

Latour (2005) suggested that research using ANT should look beyond analyzing different actors based on their interests and intentions. Instead, it can focus on how actions are coordinated between actors and non-human actors within social networks. This perspective is interesting because Latour emphasized that social networks do not contain fixed groups but rather dynamic group formations. In other words, groups are continuously formed and reformed through interactions. To distinguish a group within this framework, a “spokesperson” should represent the group’s existence, which resembles the emerged main themes and influencers on social network platforms. This approach highlights the flexibility and ever-evolving nature of group identities in networked environments.

ANT can provide insights into how social media platforms such as Twitter are used by advocates to communicate information with each other and coordinate actions. By studying the ever-changing groups in the network, ANT can guide us to identify the “spokespersons” (leading influencers) in the social network (Latour 2005). Guided by ANT, we raised Research Question (RQ) 1: Which actants play a leading role in shaping the discourse of SB147 on Twitter?

2.2 Culturally grounded scapegoating and Asian community in the post pandemic era

Kenneth Burke defined scapegoating as a rhetorical strategy to address societal guilt by selecting an individual or a group to blame (1970). Specifically, scapegoating involves attributing blame to an undeserving individual, group, or object to rationalize some society member’s own failure (Burke 1970; Girard 1986). Through this process, the society’s members who select a scapegoat can maintain social structure, or in Burke’s term, maintain hierarchies (Burke 1970).

Glick (2005) further defined scapegoating as “an extreme form of prejudice in which an outgroup is unfairly blamed for having intentionally caused an ingroup’s misfortune (p. 244).” In other words, the notion of scapegoating has been extended to intergroup conflicts, particularly in examining host countries’ attitudes towards immigrants (Goodfellow 2020). Immigrants are often blamed when the natives have low subjective well-beings: “Aversive life circumstances…may evoke stress and negative affect, causing people to react to such stressors or frustration with hostility and aggressive cognitions…they may instead displace their aggression toward an innocent target (Korol et al. 2023, p. 4).” Scapegoating also arises in situations where certain groups are perceived as taking jobs or resources from natives, especially during financial crises. The natives in the host countries blame immigrants for high unemployment rates or economic downturns, with negative attitudes towards immigrants intensifying in worse economic crisis (Goodfellow 2020; Isaksen 2019).

The most significant findings from research on scapegoating and immigration is the reciprocal relationship between political distrust and anti-immigrant attitudes over time (Goodfellow 2020; Korol et al. 2023). Korol and colleagues’ research in Sweden showed a strong link between native young adults’ exclusionary attitudes towards immigrants and their political disenchantment (2023). Their findings resonated with Aschauer and Mayerl (2019) study, which used data from the European Social Survey across twenty-one countries and found that individuals with a high level of political distrust reported higher level of threats from immigrants. Consequently, mainstream groups are more likely to adopt an ethnocentric mindset, strengthening the bonds within their ingroups and are more prone to support right-wing parties on their anti-immigrant policies.

The scapegoated groups often possess relatively low political power and are perceived as different from the societal mainstream group (Glick 2002). In fact, the Asian community has always been viewed as both different and external, situating a position of low political power within the U.S. society, a perception that exists not only historically but also in contemporary times (Kim 1999). From 1882 to 1943, the U.S. Congress prohibited Chinese immigrants from becoming naturalized U.S. citizens (Chinese immigration and the Chinese exclusion acts, n.d.). During World War II, Japanese American were scapegoated and incarcerated in internment campus. In the context of COVID-19 pandemic, scapegoating can be used to explain racist and violent incidents towards the Asian community, as people tend to blame an external group in the uncertain and turbulent situations (Omori and Stitt 2023; Tahmasbi et al. 2021).

Scapegoating during the pandemic manifested in two primary ways: (1) verbally blaming Asian Americans, specifically Chinese Americans, for causing of the pandemic, and (2) physically shunning them as virus carriers. A significant number of violent attacks were reported by Asian Americans and/or people with Asian descents during the pandemic (Borja et al. 2020; Cheng et al. 2020; Chung 2021). Meanwhile, a growing body of scholarships has examined the activism against Asian hate and Asian community’s racial tension and struggles during the pandemic through a culturally scapegoating lens (see Omori and Stitt 2023; Chung 2021).

Considering that SB147 emerged in the post-pandemic era and specifically targeted certain ethnic groups, the current project aims to examine the discourse surrounding SB147. It seeks to understand the continuity of scapegoating dynamics and their impact on the Asian community. In examining SB147, our analysis critically assesses the language and implications of the proposal, unpacking how SB147 participates in and perpetuates narratives of xenophobia, exclusion, and discrimination. Through a scapegoating perspective, we will explore the complex ways in which legislation affects communities. This approach intends to provide a better understanding of how government bills can shape and reinforce the complex matrices of power and oppression.

It is important to note that Twitter has become a prominent communication platform between politicians and voters (see Hemphill et al. 2021), allowing politicians to craft their electoral profiles (Terán and Mancera 2019), demonstrate their policy positions (Giger et al. 2021), and signal voting preferences (Mousavi and Gu 2019). Moreover, the communication between politicians and Twitter users is reciprocal. Politicians’ statements on Twitter could affect the public’s cognitive and affective reactions (Lee and Shin 2012; Lee et al. 2020), while users can voice their views on government policies and legislative bills (see Lee and Shahin 2023; Dai and Higgs 2023).

With the emergence of #SB147 on Twitter, we chose to investigate the online public discourse surrounding SB147, guided by the scapegoating theory. We propose the second research inquiry: What prevalent themes emerge in tweets related to SB147, and how does the public discourse reflect the principles of scapegoating theory?

3.1 Sample of tweets

To answer the research questions, we collected tweets related to SB147 from publicly accessible Twitter accounts. The data collection spanned a duration of six months, commencing on November 14, 2022, concluding on May 27, 2023. This time frame was strategically chosen to encompass the period from the bill’s introduction to its rejection within the Texas State House. This allows us to capture the central discourse surrounding SB147.

Tweets containing the term “Senate Bill No. 147” or “SB 147” were minded using a Microsoft Excel add-on and open-source tool, NodeXL Pro, which uses Twitter’s Application Programming Interface (API). We extracted the tweets in early June 2023, and although access was limited, the Twitter API was still operational. NodeXL Pro generates network visualization, and it helps researchers to understand how interactions are performed between different actants. In total, 2,534 users and 12,641 tweets appeared within this time frame. Direct tweets accounted for 577 (∼4.6 %) and retweets accounted for 12,064 (∼95.4 %) for all the tweets. In the analysis, we treated tweets and retweets the same.

The majority of the tweets collected in our dataset were composed in English language, with about 8 % of the tweets composed in Chinese. To ensure a comprehensive analysis, our approach involved initially subjecting all collected tweets to semantic analysis utilizing the NodeXL Pro. Subsequently, we proceed to translate the Chinese terms/word pairs identified by NodeXL Pro into English. The rational for not undertaking the translation of Chinese tweets into English prior to the semantic analysis from the concerns that contextual meanings could potentially be lost during the translation process. By initial conducting the semantic analysis, we could preserve the integrity of the original Chinese tweets. Ultimately, our analytical process culminated in a comprehensive examination of all words and word pairs extracted from the tweets. This holistic analysis served as a crucial step in gaining a better understanding of the content and thematic underpinnings inherent in online discourse.

3.2 Top influencers and emerging word pairs

Social network analysis (SNA) explains the relationships (ties) among social entities and the patterns of social interaction (nodes) (Yang et al. 2017). SNA provides insights into the structures of social networks, showing how individuals and groups interact within a given network. Employing SNA, the current project explores the interactions between different Twitter actants (users) surrounding the discourse of SB147. The SNA was conducted using NodeXL Pro. To answer RQ1, which focuses on identifying top influencers, we identified the top 30 influential Twitter users within the network.

The level of influence was measured by PageRank. PageRank is a metric that explains the importance of nodes based on their connectivity. In other words, PageRank calculates the connectivity by measuring the numbers of mentions and/or retweets a user receives from others. Ultimately, Twitter influential users who are mentioned and/or retweeted more frequently in the network are considered influential actants and receive higher PageRank scores. This measurement helps identify which users are more influential in disseminating information or shaping discussion within the SB147 network. Based on ANT’s definition of actants, we identified the 30 most influential actants and classified them into two categories: human actor accounts and non-human actants accounts. To be more specific, SNA allowed us to answer RQ1 by identifying top influencers and analyzing the types of them, as well as their influence in shaping SB147 online discourse.

To answer RQ2, we applied semantic analysis to investigate the viewpoints of Twitter users regarding SB147. Semantic analysis enabled us to reveal prevalent words and word pairs that frequently appeared within the corpus of tweets under examination. We interpret the meanings of the recurring words and word pairs by exploring how they are semantically connected. At this stage, word pairs were analyzed as vertices and edges, where vertices represent the entities and edges refer to the connections between these entities. The frequency of occurrence of each word was quantified using the metric of Count, while the Salience metric assessed the significance of the words within the network. This is an inductive and interpretive process, which aims to elaborate the themes emerged from different groups of words/words pairs.

4.1 Top influencers

Through social network analysis, we identified the top 30 influencers of the SB147 network. Guided by ANT, we categorized these influencers as human actors and non-human actants; and proponents and opponents of SB147 based on their profile information and the tweets they posted and/or engaged with (Table 1).

Table 1:

Top 30 influential actors.

No	Twitter (X) account ID	Position of SB 147	Human actant or non-human actant
1	Son of David (@drolusesan)	Neutrality	Human actant
2	Gene Wu (@genefortexas)	Opponent	Human actant
3	小径残雪 (@xiaojingcanxue)	Proponent	Human actant
4	Merissa_Hansenus(@merissahansen17)	Proponent	Human actant
5	Stop AAPI hate (@stopaapihate)	Opponent	None-human actant
6	Petrichor (@jam79922967)	Proponent	Human actant
7	Senator Lois Kolkhorst (loiskolkhorst)	Proponent	Human actant
8	Luciafight for Trump老娘就是川粉 (@choolucia)	Proponent	Human actant
9	AALC (@aalc)	Opponent	None-human actant
10	Becky Werner (@bw71961)	Opponent	Human actant
11	Lisa Xin 子涵 (@lisaxinsohradio)	Proponent	Human actant
12	Inconvenient Truths by Jennifer Zeng 曾錚真言 (@jenniferzeng97)	Proponent	Human actant
13	Hello world (fo) (@whitetony99)	Opponent	Human actant
14	XuYiChuan Xu (@xuyichuanjune)	Opponent	Human actant
15	Bob Fu 傅希秋(@bobfu4china)	Proponent	Human actant
16	Kenny Webster (@kennethrwebster)	Proponent	Human actant
17	方伟|Allen Zeng (@sohfangwei)	Proponent	Human actant
18	Bin Xie (解滨)TheGreatTranslationMovement (@bxieus)	Proponent	Human actant
19	彼埠 Embarcadero(@embarcaderous)	Opponent	Human actant
20	Velourit (@velour_it)	Proponent	Human actant
21	Mihaela E. Plesa HD70 (@plesafortexas)	Opponent	Human actant
22	Aaron Reichlin-Melnick (@reichlinmelnick)	Opponent	Human actant
23	Francine Ly for Congress (@flyforcongress, now @FlyForCongress).	Opponent	Human actant
24	Chinese for affirmative action (@caasanfrancisco)	Opponent	None-human actant
25	Woori Juntos (@woorijuntostx)	Opponent	None-human actant
26	Patrick Svitek (@patricksvitek)	Opponent	Human actant
27	Luke Q. Malace (@lqmalace)	Proponent	Human actant
28	Rise AAPI (@riseaapi)	Opponent	None-human actant
29	Nick Gee (@nicholasjgee)	Neutrality	Human actant
30	Anahita (@anahitaahmadi3)	Opponent	Human actant

Our analysis identified 25 human actants (individuals) and 5 non-human actants (organizations) as top influencers in the network. Prominent among the human actants are Texas State Representative for District 137, Gene Wu; Texas State Senator Lois Kolkhorst; Texas State Representative for Collin County, Mihaela E. Plesa; and Francine Ly, a Democratic candidate for Texas District-24. These individuals are government officials and politicians. In terms of their positions on the bill, Republican Sen. Kolkhorst, who introduced the bill, support SB147, while Gene Wu, Mihaela E. Plesa, and Francine Ly have expressed strong opposition.

In addition to the aforementioned political figures, our analysis revealed 11 individual human actants supporting SB147 and 6 individual human actants opposing it within the top influencer network. Interestingly, 6 of the Pro-SB147 influencers are Chinese American or individuals of Chinese descent living in the U.S., such as Petrichor and Bin Xie. On the other hand, several Con-SB147 actants described themselves as immigrants’ rights advocate, with including hashtags such as #StopAsian Hate or #StopRacism in their bios, examples being XuyiChuan Xu and Nick Gee. Anahita, another Con-SB147 human actants, was the only account that associated with people of Iranian descent. Son of David” and Patrick Svitek maintained neutrality on SB147.

Moreover, organizational non-human accounts such as Stop AAPI Hate, the Asian Americans Leadership Council (abbreviated as AALC), Chinese for Affirmative Action, the Texas-based AAPI support group Rise AAPI, and the local community-based organization Woori Junto were identified among the top influencers. All of these organizations are positioned on the Con-SB147 spectrum.

4.2 Emerging themes

In the SB147 network, 10,261 words and 14,256 word pairs emerged, with counts ranging from 4,113 to 3 and 601 to 2 respectively. Salience for these ranged from 0.007 to 0. After cleaning irrelevant terms such as “e.g.”, “amp”, “rt”, and “http”, we focused on word pairs that appeared more than sixty times. These significant word pairs were categorized into fifteen sub-groups (Figure 1).

Figure 1:

Word pairs repeated more than 60 times in SB147 network.

Among these subgroups, the fifth group (G5) primarily consisted of textual content composed in Chinese characters, while the remaining groups written in English. To ensure uniformity in the analysis of findings across all fifteen sub-groups, we translated G5 into English. The translation process was completed by the authors, who are fluent in Chinese. Moreover, we engaged in collaborative discussions to reach a consensus regarding the translated content. With the support of NodeXL, English words are analyzed as single word in semantic analysis, whereas Chinese words are analyzed as cohesive clusters (Table 2).

G1 stands out as the most extensive word group within the semantic network. As one of the top influencers, “genefortexas” (Texas House representative Gene Wu) situated in a key position in G1. Wu has consistently voiced his opposition to SB147 ever since its inception as a legislative proposal in the State Senate. His public denunciation of the bill has been a recurring feature in the discourse, and he conveyed disappointment when the bill successfully passed through the State Senate in April 2023. Words like “teamfly4texas”, “district”, and “activists” referred to the advocacy from Democratic candidate for Texas District-24 – Francine Ly, who is also one of the top influencers. Francine Ly has articulated her position on SB147 and demonstrated her commitment to opposing it by orchestrating rallies on March 11, 2023, in Stanford, Texas. Furthermore, she employed #StopAsianHate in her tweets, which directly indicated her stance on SB147 and her advocacy against discriminatory and exclusionary elements within a subset of proposed bills.

Words like, “senate”, “kolkhorst” “loiskolkhorst”, “hearing”, and “induced” emerged in both G2 and G3. This resonated with the proposed bill SB147 that was introduced to the public by Sen. Kolkhorst. In fact, prior to SB147 being enacted into law in Texas, it required public “hearing(s)” for consideration. The first hearing for SB147 was held on March 2, during which advocates from both sides (Pro-SB147 and Con-SB147) testified.

Furthermore, within the context of G3, the term “jenniferzeng 79” emerged, referencing the account of Inconvenient Truths by Jennifer Zeng. Jennifer, one of the top influencers, expressed her support for SB147 in her tweets and provided observation about the March hearing. For instance, her tweet posted on March 5 garnered substantial attention, receiving 166 likes and over 8,590 views.

Within G2, terms such as “SB552”, “HB1075”, “buying”, “purchasing”, “land”, and “legislator” also emerged prominently. SB552 and HB1075 were introduced by a collective of legislators in Texas shortly after Sen. Kolkhorst’s proposal of SB147. These bills represented significant resemblance to SB147, albeit with more specific details. Both bills recommended the implementation of regulations or bans preventing foreign governments from China, Iran, North Korea, and Russia from accessing agricultural land within Texas (Scott 2023).

It is important to acknowledge that there is a visible link between G2 and G5. Words in G5 mainly came from the tweets of Petrichor. Petrichor, one of the top human actant account, that used pseudonyms and tweeted in Chinese. It wrote,

Bans citizens of China, Iran, North Korea, and Russia from buying homes and land in Texas! (Pro-SB147 and Pro-SB552). Texas Governor Abbott expressed his willingness to sign this bill on the grounds that it prevents these countries from threatening our infrastructure. Some Chinese took to the streets, encouraged by the Chinese Communist Party’s big foreign propaganda, to equate the ban on buying land with racial discrimination. Are foreigners allowed to buy farmland and infrastructure in China? In fact, the Chinese Communist Party discriminates more heavily against foreigners.^[1]

This was posted on January 29, and it was retweeted 83 times by other users, received 134 replies, and had 534 favorites (likes) in the network. This tweet served as an informational bridge between English and Chinese news, providing Chinese-speaking Twitter users an understanding of the bill. It also captured the words of “Governor Abbot”, “willing to sign the bill”, “into law”.

Words in G4, “exclusion”, “serious”, “consideration” came from AALC. AALC is an is a leading organization campaigning against the discriminatory SB147 and SB552. AALC was also featured among the top influential actants in the network analysis, and it also advocated Equality and Stop Asian Hate. AALC clearly denounced SB147 was a new Chinese exclusion bill, and it was a “blunt discrimination on Chinese Americans and other minority communities.”

Meanwhile, “exclusion” (G4) exhibited a notable association with “chinese” (G6). Additionally, words like “american(s)”, “citizens”, “asian”, “community”, “anti”, “aapi”, “rally”, “against”, and “solidarity” were prevalent within G6. These terms collectively alluded to the response of Asian American community, which organized opposition to SB147 and held rallies of “Say No to SB147” in various Texan cities, including Houston, Dallas, and Austin, during the month of February. A notable link exists between G6 and G9 centered around the term “immigrants”. Moreover, a link exists between G6 and G10, which centered around the term “community”.

Additionally, words like “people”, “abortion” (11); “united”, “states” (G12); “north”, “korea” (G7); “communist” “party” (G14), and “civil”, “rights” (G15) prominently emerged in the semantic analysis. These specific word pairs encapsulated the salient subjects under discussion within the SB147 social network.

5.1 Theoretical contribution

The social network analysis conducted within the context of the SB147 discourse has revealed a list of the top 30 influential actants on Twitter, which includes twenty-five individual human actants and five non-human organizational actants. These actants have demonstrated significant level of engagement with the discourse surrounding SB147 and the living conditions of the Asian community in the U.S. These findings align with Walsham’s (1997) interpretation of ANT, which suggests that actants encompass not only human beings and organizations but also various non-human entities.

Among the individual actants, four hold governmental positions, primarily as elected representatives affiliated with the Democratic Party. Sen. Kolkhorst, the main sponsor of the bill, is the only Republican politician featured within the network. Although Governor Greg Abbott, also a Republican, indicated his intention to sign SB147 into law should it pass the state legislature, his Twitter account did not emerge as one of the top influencers in the discourse. In terms of organizational actants, five entities were prominent, including non-profit coalitions such as Woori Juntos and organizations with political propositions, such as AALC and Chinese for Affirmative Action. Notably, these organizations adopt a broad and inclusive approach, addressing a wide range of issues concerning Asian Americans and Asian immigrants, rather than focusing on a single issue.

Drawing upon the foundational concept of agency within ANT, we suggest that government officials and politicians can be viewed as organizational actants, albeit in the form of non-human actants. This characterization reflects the recognition that the actions and expressions of these actants on digital platforms are highly influenced by their political ideologies. Moreover, their political affiliations significantly impact their support or opposition to initiatives like SB147. In the current political atmosphere, the polarization of partisan divisions has become increasingly conspicuous (see Liu 2020; Enos 2018). For instance, members of the Democratic Party may oppose a proposal because it is filed by Republicans, as seen when Senate Republicans blocked an In Vitro Fertilization (IVF) bill in September 2024 (Walsh 2024). Similarly, Democrats rejected Republicans’ 2025 Interior, Environment, and Related Agencies funding bill in 2024 (Appropriations Committee Democrats 2024). Therefore, political ideology and partisan alignment assume a pivotal role in shaping the perspectives and behaviors of these organizational actants.

Furthermore, more than half of the influencers were aligned against SB147, openly expressing their reservations and disapproval of the proposed legislation. Notably, some of these influencers were also advocates for #StopAsianHate, #StopRacisim, and/or standing in solidarity with AAPI community. The dual commitment demonstrates their core ideological beliefs in equality and equity, coupled with a genuine concern for the welfare of minority and/or marginalized populations within American society. In contrast, Sen. Kolkhorst emerged as one of the top influencers, voicing strong support for SB147. Sen. Kolkhorst reinforced the belief that SB147 was instrumental in safeguarding the national security interests of the U.S.

Within the framework of ANT, non-human actor technologies (e.g., Twitter) influence human actor’s behaviors and vice versa (Vicsek et al. 2016). In our analysis, we identified Twitter as a non-human actor due to its nature as a social media platform or technology entity. In the context of a contentious issue like SB147, Twitter became a political battleground for various parties, where different perspectives were expressed and interwoven. It is worth noting that the top influencers were not isolated entities, instead, they were interconnected through interactions such as commenting, retweeting, or mentioning each other in the network. For instance, XuYichuanXu mentioned Gene Wu and Lois Kolkhorst, and several Con-SB147 accounts mentioned Gene Wu. These connections among the top influential actants contributed to the formation of what Brunner and Partlow-Lefevre (2020) have termed “wild public networks.”

5.2 Scapegoating and Asian community in the U.S.

The themes of concerns, discrimination towards the Chinese community and broader Asian community, and political nepotism emerge within the analysis. The opponents of this bill contend that SB147 encompasses provisions that have the effect of excluding certain demographic groups from purchasing property. Such exclusionary measures are regarded as instances of discrimination – the unjust treatment of different categories of people, especially on the grounds of ethnicity, age, sex, or disability (Fujiwara and Roshanravan 2018). For instance, one tweet specifically called out this perception of unjust treatment, “We are no scapegoat!! We demand equality! Fair housing is basic human right!! No to #SB147, No to #SB552.”

We also found that since the bill’s introduction, the Asian community has assembled protests online, including on Twitter, and organized rallies in Texas cities such as Austin, Houston, and Dallas. The terms “exclusion”, “asian”, and “aapi” repeatedly emerged in the analysis. Analyzing these findings through scapegoating theoretical framework highlights the systemic power dynamics and discrimination faced by Asians Americans and individuals with Asian decent living in the U.S. Given the hostile environment towards Asian American and Pacific Islanders (AAPI) since the pandemic, SB147 could further inflame an already heated situation. This perspective also shed lights on the struggles against legislative measures that perpetuate discrimination and xenophobia, reinforcing the necessity for a nuanced understanding of how such laws intersect with race, gender, class, and other identity markers. Meanwhile, it highlights the importance of solidarity and activism of Asian Communities in challenging the social hierarchy.

Moreover, many terms associated with the Pro-SB147 perspectives emerged in the semantic analysis, including “Texas Governor Abbott has indicated his willingness to sign the bill”, “Prevent these countries from threatening our infrastructure”, and “Promoting agricultural security and safety”. Supporters of the bill believe that protecting national security is very important. They believe that allowing citizens from countries such as Iran, North Korea, Russia, and China, regardless of their immigration status within the U.S., to acquire land or property in Texas would pose a significant threat to American safety and national interests. This reflects a form of scapegoating, targeting members of society who are perceived as politically weaker or having less power.

A possible explanation for the support of SB147 is that it serves as a form of scapegoating. Scapegoating suggests that mainstream groups, which favor hierarchical social structures and the maintenance of unequal intergroup relations, tend to view individuals from outgroups – such as immigrants and ethnic minorities – as inferior. The success and advancement of these outgroups, particularly immigrants and marginalized minorities, are perceived as a threat to their status quo. As a result, feelings of antipathy and antagonism towards the outgroups can be easily identified among those individuals (Korol et al. 2023). The mindset leads to proponents of SB147 to express resentment and blame towards individuals of Asian descent in their online discussions, using this as a justification for their support of the legislative proposal.

A more in-depth examination of the topics emerged from the discourse reveals an interesting phenomenon where certain conversations supporting SB147 originate from accounts identified as someone with Asian descent, particularly with Chinese descent. Several of their tweets advocating for supporting SB147 received a lot of attention within the network. In the context of the individuals with Asian descent supporting SB147, their stances may be a reflection of their unique acculturation experiences, where they have chosen to adopt an assimilation strategy, emphasizing alignment with mainstream cultural values and objectives. This choice can influence their perspectives on policies like SB147, even if it appears contrary to the interests of their ethnic ingroup. It is absolutely true that Asian Americans are fellow Americans, and they are different from individuals living in their respective Asian countries of origin. However, it is deeply concerning that many individuals with Asian descent have become targets of prejudice and hate crimes due to mistakenly viewed as “Chinese” (Tessler et al. 2020; Omori and Stitt 2023).

In line with these issues, we suggest that it is not prudent for Asian American and individuals with Asian descent to support SB147 or similar initiatives. We believe that solidarity among minority ethnic groups is crucial. The phenomenon of scapegoating often leads mainstream groups to homogenize outgroups, ignoring the diverse differences within those groups. Supporting proposals like SB147 and similar legislation could exacerbate the challenges faced by Asian Americans and individual of Asian descent. Additionally, such legislations will reinforce the hostile attitudes and experiences encountered by Asian community encounter in their daily lives and perpetuate racial stereotypes.

Additionally, the perspectives of citizens hailing from Iran, North Korea, and Russia was almost silent from the discourse, except tweets from Anahita. Their absence may be attributed to a confluence of factors that warrant our examination. First, these three countries have relatively smaller immigrant population within the U.S. compared to the Chinese community. Second, it is imperative to acknowledge that citizens of North Korea and Iran have limited access to the internet outside their countries. Third, due to the contextual influence of the Russo-Ukrainian war, Russia was associated with extreme negative country image on the internet.

5.3 The failure of SB147 and outlooks

As discussed above, Twitter has served as a non-human actor and technology entity, transforming into a political battleground. It is noteworthy that more than half of the top influencers were aligned against SB147. These accounts were interconnected, forming the “wild public networks” that amplified their voices. We believe that the resistance and activism of the prominent opposing influencers on Twitter, including several politicians and lawmakers, played an important role in raising public awareness and influencing legislative decisions. Furthermore, the online public discourse surrounding SB147, which emphasized demands for equality and equity and rejected scapegoating based on ethnicity, strengthened opposition to the proposed bill. This collective action on Twitter contributed to the defeat of SB147 in the Texas State House Committee and subsequently in the State House on May 24, 2023.

Although the proposed bill SB147 ultimately failed in Texas, it is undeniable that SB147 has ignited a degree of controversy, triggering a chain reaction within the contemporary American society. On March 23, 2023, the South Carolina State Senate passed SB576, a legislative initiative aimed at restricting land ownership by foreign nationals, specifically Chinese citizens (including legal permanent U.S. residents, legal visa holders and asylum seekers) and business from owning property in the State of South Carolina. On April 11, 2023, the Florida State Senate passed SB264, which imposes a prohibition on companies associated with China, Iran, Russia, Venezuela, Syria, Cuba, and North Korea from engaging in business transactions with Florida’s government. Additionally, other states, including Virginia and Florida, are considering similar legislation aimed at curbing foreign land acquisitions.

With these series of bills, we believe that SB147 and related legislative actions do not exist in a vacuum but are situated within a broader historical context of race and ethnicity-based discriminations. These bills echo of “Alien land laws” in the U.S., highlighting the legacy of exclusion and margination of Asian community, and potentially subjects the broader Chinese community to discrimination. This historical reference alludes to xenophobic sentiments that portray Asian communities, particularly those of Chinese descent, as a perceived threat to the American society. As such, these contemporary legislative measures have reignited uncertainties and fears that such discriminatory practices may resurface. The targeting of foreign nationals and businesses associated with certain countries inherently affects those who are already vulnerable, including women seeking asylum, visa holders, and legal permanent residents. This exacerbates their challenges in an environment that is already difficult to navigate.