Facebook Posts Research Articles

A Netnographic Study on The Reasons Why People Fail to Learn English

In a global and digital world, learning a language, especially English is essential for people to keep up with the developments in science, business, technology, etc. Despite starting to learn English early, students might not always reach desired proficiency levels. Therefore, the present study aims to find out some of the reasons why people fail to learn English. Employing a netnographic approach, the researchers examined asynchronous comments posted in online communities on a social media platform. Within the scope of this study, 198 comments answering the question of why people fail to learn English were obtained from three online groups of English language teachers on Facebook. The findings show that 154 out of 198 comments aimed to answer the question. They were analyzed through content analysis, which revealed that there are educational, social, personal, and linguistic reasons why people fail to learn English. Educational reasons were among the most mentioned reasons by the members of the communities. In addition, the analysis indicates a balanced representation of linguistic and personal factors, with social factors slightly less prominent in comparison. Considering the existing literature review, several implications are highlighted to overcome the difficulties and challenges of learning English. Finally, this study is limited by its reliance on Facebook posts collected within a specific timeframe; future research could enhance depth and scope by incorporating longitudinal methods, diverse social media platforms, and in-depth interviews.

Confronting and (Re)constructing “Conquest Culture” in Outdoor Adventure: A Critical Analysis of #Microadventure Content on Facebook and Instagram

Underpinned by Romantic wilderness ideals and American settler colonialism, recurring themes of “conquest culture” in outdoor adventure—social privilege, individualism, and exploitation—are carried out on social media. This study explores how an emerging topic, microadventures, may reinforce or resist these dominant discourses in outdoor adventure. Facebook and Instagram posts tagged “#microadventure” were collected and analyzed using a qualitative critical social media content analysis informed by Hall’s (1973) Theory of Encoding and Decoding. We found that half of the posts reinforced conquest culture, while the other half resisted. The discussion of our findings, framed as a critique of neoliberalism, seeks to interrogate, from a U.S. perspective, how conquest culture is perpetuated by representations of adventure across the global social media landscape. Our findings suggest the need to deconstruct market-driven, colonial tendencies in outdoor social media by (1) confronting dominant conquest discourses and (2) (re)constructing neoliberal tendencies in the outdoor field.

Engaging with underserved communities during times of crises: A computational analysis of social media interactions with government information about COVID-19 economic relief programs

Racial and social inequalities in the digital landscape remain pressing concerns in society. Previous research on government efforts to address digital inequality has largely focused on improving access to digital infrastructure and literacy. However, there is a severe shortage of research that examines how underserved communities engage with government information on relief measures and policies during crises. This study fills these gaps by drawing insights from three bodies of literature – digital inequality, the situational theory of problem solving, and fear. We investigate how underserved communities, such as low-income individuals, communities of color, and rural populations, interacted with government information about COVID-19 economic relief programs designed to mitigate the adverse effects of crises, and how fear influenced public engagement patterns. We analyzed Facebook posts (N = 28,887) containing links (URLs) to government websites on COVID-19 economic relief programs from 2020 to 2022. Our findings show that posts shared within underserved communities generated higher levels of engagement (shares, comments) compared to those shared in nonunderserved communities. This indicates that underserved communities showed great interest in and participation with government information about relief programs during the pandemic. Notably, engagement significantly decreased when fear was expressed in discussions, and such a pattern was more pronounced in underserved communities than in nonunderserved ones. These results offer valuable insights into the communication dynamics of underserved communities during crises, contributing to a deeper understanding of digital inequality within the policy context.

Data-Campaigning on Facebook: Do Metrics of User Engagement Drive French Political Parties’ Publications?

Research on data-driven campaigning has mostly focused on the strategies of central campaign teams. However, there is a lack of evidence explaining how parties and supporters use data-driven campaigning techniques to organise their social media campaigning. Do user engagement metrics influence the choice of campaign themes by encouraging political parties to concentrate their communication on issues that are most liked, commented on, and shared? Our study focuses on the use of Facebook by French political parties and their supporters during the 2022 presidential election campaign. We conducted a supervised content analysis based on machine learning to examine their Facebook posts (<em>n</em> = 17,060). Our results show that the issues prioritized by parties on Facebook may be different from those that are most prominent in their broader communications. In most cases, however, these themes are not chosen based on user engagement, even for parties that claim to have developed their base through digital channels. Instead, the choice of themes seems influenced by more traditional campaign strategies, such as the desire to capture the electorate of their closest rival. In our conclusion, we discuss the implications of these findings for the adoption of data-driven campaigning in digital election communication across Europe.

Enhancing public engagement through NICU storytelling on Facebook and Instagram: a case study from Gaslini Children’s Hospital

BackgroundSocial media platforms, particularly Instagram, have become pivotal in disseminating medical information to the public. However, the challenge of presenting neonatal intensive care unit (NICU) stories in a manner that is both engaging and informative remains significant, especially in the context of a reputable pediatric hospital.ObjectiveThis study aimed to explore the effectiveness of Instagram as a storytelling medium for NICU experiences at the Gaslini Children’s Hospital, focusing on the impact of various storytelling elements on audience engagement and follower growth.MethodsWe analyzed Facebook and Instagram posts of the Gaslini Children’s Hospital, examining factors such as emotional appeal, news value, and content quality. Additionally, we considered the adherence of these posts to journalistic and medical guidelines.ResultsThe research identified key themes in successful posts, including emotional resonance, portrayal of medical excellence, and humanization of patient stories. Posts that effectively combined these elements saw a significant increase in audience engagement, including likes, comments, and shares.ConclusionStrategic storytelling on Instagram can significantly enhance public engagement with hospital content, fostering a deeper connection between the institution and its audience. This study underscores the significance of narrative elements and adherence to ethical guidelines in crafting compelling medical stories for social media.

The polarized “naturalizations” of the 2022 Freedom Convoy

During the month-long “Freedom Convoy” protest in Ottawa (Canada), protesters were ascribed many attributes (violent, extremist, hateful, disinformed) which they refuted. Protest organizers insisted the Freedom Convoy was peaceful, loving, and included “average Canadian citizens fighting for freedom”. This research is interested in the construction of this representational divide and its consequences. It analyzes the polarized social representations of the COVID-19 Freedom Convoy by using social representation theory, and more specifically, Negura and Plante’s model of “naturalization”. News articles (n = 516) from Canadian media and Freedom Convoy organizers’ Facebook posts (n = 611) were submitted to a rhetorical frame analysis. Results show how communications from organizers and the media both contributed to the naturalization of conflicting representations by (1) associating the movement with a desirable/undesirable identity, (2) neglecting nuanced perspectives, (3) instrumentalizing their representation to justify the legitimacy/illegitimacy of the protest, and (4) validating the representation by focusing on incidents that ratified the Freedom Convoy’s “goodness” or “badness”. We argue that this single protest became two opposed and morally charged “objects” impossible to reconcile, which prevented dialogue. Social implications of polarized naturalizations during epidemics are discussed.

THE IMPACT OF SENTIMENT ON USER’S REACTION ON FACEBOOK: THE CASE OF THE AMERICAN CHAMBER OF COMMERCE IN UKRAINE

This study investigates the relationship of sentiments expressed in Facebook posts by the American Chamber of Commerce (ACC) in Ukraine on audience reactions. By employing AI-driven sentiment analysis, we categorize ACC's posts into five categories: Empowerment category, Excitement and enthusiasm category, Gratitude category, Optimism category, and Resilience category. Our findings reveal that posts signaling resilience and optimism receive significantly more reactions compared to those communicating empowerment and excitement. As sentiment analysis continues to evolve, incorporating multimodal approaches and leveraging advancements in AI and NLP, businesses that effectively utilize these tools will be better equipped to make informed decisions and adapt to the ever-changing digital landscape. Furthermore, posts classified as displaying empowerment are more likely to be shared/reposted by the readers. These results highlight the importance of tailoring communication strategies to elicit desired audience responses and provide valuable insights for organizations navigating complex environments.

Saving the Wild or Saving the Cowboy? Cultural Conflict between the Old and Nouveau West*

AbstractIn North Central Montana, a land‐based conflict centered on the environmental organization American Prairie sparked the formation of the “Save the Cowboy, Stop the American Prairie Reserve” Facebook page, attracting posts and comments from ranchers and members of the area's agriculture‐dependent communities. Despite Montana's rapid amenity migration and rural gentrification, this region has largely maintained its Old West culture. Consequently, Save the Cowboy members often express frustration about how American Prairie's large‐scale rewilding initiative and land acquisitions affect the region's rural communities. In this qualitative content analysis, concerns about preserving the Old West culture and avoiding the New West transformation dominated Save the Cowboy's Facebook posts and comments (N = 1,002), even compared to the ostensibly more concerning economic and ecological issues. By describing a social space marked by cultural antagonisms between Old West insiders and New West outsiders, this study points to the dangers of essentializing Old West‐New West conflicts. Illustrating how Old West insiders deploy their cultural capital to contest rural change, it also expands the Old West‐New West typology by proposing the term “Nouveau West” to capture how Old West insiders assert dominance by disparaging newcomers who lack the requisite knowledge of how things are done locally.

Climate Change Advocacy and Engagement on Social Media

This study examines how 21 leading environmental organizations framed climate change on Facebook and how these frames were associated with public engagement through reactions (e.g., likes), shares, and comments on the posts. We find that environmental nongovernmental organizations’ (NGOs) posts about climate change tend to emphasize the environmental impacts of climate change, political actions that are being taken by individuals and groups to address climate change, and political threats to climate progress. The results tentatively suggest that Facebook posts with an affective component—either positive or threat-based—are most likely to be associated with greater levels of engagement.

Exploring emotional dynamics: Word count effects in Facebook posts by sports shoe brands

This study examines the impact of word count in Facebook posts on user engagement and emotional responses, focusing on sports shoe brands. It addresses a research gap concerning the effects of post length on various emotional aspects and engagement metrics within social media marketing. Data were collected from January 1, 2024, to January 30, 2024, covering posts from January 2013 to December 2023 on official Facebook pages of several sports shoe brands. After cleaning an initial 723 posts, 636 were analyzed using statistical methods and Python libraries. Eight emotional aspects—fear, anger, sadness, trust, anticipation, joy, disgust, and surprise—were examined in relation to post length. Mean reaction values and emotional aspects were compared before and during the COVID-19 period. A structured equation model (SEM) in AMOS assessed these relationships. The analysis revealed that longer posts positively influenced trust (β = 0.208, ρ < 0.001), anticipation (β = 0.095, ρ < 0.05), joy (β = 0.259, ρ < 0.001), and surprise (β = 0.072, ρ < 0.05), but did not significantly affect fear (β = 0.065, ρ = 0.089), sadness (β = 0.054, ρ = 0.155), or disgust (β = 0.072, ρ = 0.116). During COVID-19, increased trust and anticipation were noted, while sadness and anger decreased. This study highlights that longer Facebook posts can enhance engagement through increased trust, anticipation, joy, and surprise, offering valuable insights for optimizing social media content strategies.

Personalized Facebook campaigning and the quest for personal votes in Taiwan

ABSTRACT Personalization is a growing trend in politics that has been well studied, yet the current literature has no causal explanations for the relationship between personalized media activities and personal votes or an understanding the contextual factors that shape it. This study examines how candidates have used Facebook as means of personalization and its impact on voting during Taiwan’s 2020 legislative campaign. It assumes that personalized campaigns originate from a need among candidates to gain personal votes and that this need is determined by the intensity of a given competition. Intensified competition between parties increases a candidate’s need for personalized activities on social media, which in turn bring in more personal votes. Through a content analysis of 27,977 Facebook posts and the compiling of data on personal votes, the models confirm two hypotheses: those in party strongholds (safe districts) are less likely to make personalized posts, and those who post more personalized messages are more likely to gain personal votes. This paper enhances our understanding of how different facets of personalization within social media are intricately linked and mutually reinforce one another in shaping voter behavior.

Hernia mesh and social media: misinformation, legal solicitation, and conflict of interest.

Patients often utilize social media platforms as a resource for medical information. Lately, hernia mesh has been surrounded by controversy due to highly publicized mesh recalls. We aimed to assess the rates of misinformation, legal solicitation, and conflict of interest of hernia mesh information on Facebook and YouTube. We conducted a cross-sectional study of Facebook posts and YouTube videos using the search term "hernia mesh." The first 150 public Facebook posts and YouTube videos were initially selected, in addition to the first 30 posts of public Facebook groups. Video/post characteristics and the presence of misinformation, legal solicitation, and conflict of interest were independently recorded by three trained raters. Fleiss' kappa coefficient (ĸ) was calculated to determine Inter-rater agreement. A total of 129 Facebook posts and 108 YouTube videos were analyzed. 29% of posts/videos were uploaded by a law firm and 24% were uploaded by medical professionals. The raters indicated that an average of 11% posts/videos contained misinformation, 17% involved legal solicitation, and 21% included conflicts of interest. Inter-rater agreement was fair for misinformation (ĸ = 0.380-0.382), substantial/almost perfect for legal solicitation (ĸ = 0.780-0.876), and moderate for conflict of interest (ĸ = 0.448-0.505). With regard to hernia mesh, misinformation, legal solicitation, and conflict of interest are somewhat common on popular social media platforms. Trained raters had a high level of agreement on legal solicitation but limited agreement on misinformation. Our findings suggest that recognizing misinformation on social media regarding hernia mesh is difficult.

Is Negative Campaigning a Response to a Dynamic Polling Environment? Evidence from Facebook and Twitter Posts by German Party Leaders in the 2021 German Federal Election

ABSTRACT Do negative campaigning strategies evolve in sync with a party leader’s position in public opinion polls? In Germany’s multi-party system, previous research during the traditional media era found that a chancellor candidate’s drop in the polls did not impact negativity. This study focuses on the dynamic campaign in the 2021 Federal Election, which is the most competitive campaign to date in the social media era as there was no incumbent chancellor candidate. The prevalence of negative campaigning by six major party leaders who made a total of n = 3580 posts on Facebook and Twitter from 1 March to Election Day on 25 September 2021 is studied here. Negative posts accounted for 7.7 per cent of total posts. Results also show that a chancellor candidate’s position in the polls matters: Front-runners are less likely to rely on negative campaigning, but as candidates drop down in the polls from being the main challenger to rank third or lower, their negative campaigning increases. During the official six-week campaign or the hot phase, the number of negative posts increases overall as Election Day approaches. Variation in the use of negative campaigning among the individual chancellor candidates is discussed as is evidence of negative campaigning prior to the hot phase.

Unpacking social media `engagement': a practice theory approach to science on social media

Social media engagement is typically associated with actions such as sharing, liking, or commenting, and is often measured as such in quantitative analyses. This essay explores what is being captured through these methods by `unpacking' such engagement, arguing for a practice-oriented approach that takes into account the mundane ways in which non-scientists may encounter and use scientific content. We describe practice theory in the context of media production and use, before illustrating the approach with material from comments on Facebook posts produced by science-related sources. In showing the uses of science content in maintaining social bonds or performing particular identities (for instance), we argue that science communication research needs to study the wider contexts of how and why users encounter science online, and that the notion of social media practices can help us to do so.

From online hate speech to offline hate crime: the role of inflammatory language in forecasting violence against migrant and LGBT communities

Social media messages often provide insights into offline behaviors. Although hate speech proliferates rapidly across social media platforms, it is rarely recognized as a cybercrime, even when it may be linked to offline hate crimes that typically involve physical violence. This paper aims to anticipate violent acts by analyzing online hate speech (hatred, toxicity, and sentiment) and comparing it to offline hate crime. The dataset for this preregistered study included social media posts from X (previously called Twitter) and Facebook and internal police records of hate crimes reported in Spain between 2016 and 2018. After conducting preliminary data analysis to check the moderate temporal correlation, we used time series analysis to develop computational models (VAR, GLMNet, and XGBTree) to predict four time periods of these rare events on a daily and weekly basis. Forty-eight models were run to forecast two types of offline hate crimes, those against migrants and those against the LGBT community. The best model for migrant crime achieved an R2 of 64%, while that for LGBT crime reached 53%. According to the best ML models, the weekly aggregations outperformed the daily aggregations, the national models outperformed those geolocated in Madrid, and those about migration were more effective than those about LGBT people. Moreover, toxic language outperformed hatred and sentiment analysis, Facebook posts were better predictors than tweets, and in most cases, speech temporally preceded crime. Although we do not make any claims about causation, we conclude that online inflammatory language could be a leading indicator for detecting potential hate crimes acts and that these models can have practical applications for preventing these crimes.

Analyzing narrative contagion through digital storytelling in social media conversations: An AI-powered computational approach

Despite the growing popularity of digital narratives, research on digital storytelling and its spread through social media interactions remains limited. Inspired by the social contagion theory, we introduce the concept of narrative contagion—where a story shared by a person or organization prompts others to share their stories—and investigate its process and outcome in online cancer communities. Utilizing a large dataset of 849 Facebook posts, 47,291 comments, and 14,466 replies, our artificial intelligence (AI)-based computational analysis provides evidence for narrative contagion among individual users in organization-hosted cancer communities on Facebook. It also reveals different organizational message characteristics, such as emotional arousal, post topic, and request for storytelling, that affect user storytelling and emotional support in comments and replies. Our results contribute to a deeper understanding of digital storytelling and its collective dynamics in online communities.

Exploring a Language-Based Interest Assessment: Predicting Vocational Interests on Social Media Using Natural Language Processing

For more than a century, self-report inventories have been the traditional method for assessing vocational interests. Little research has examined the use of machine learning techniques, such as natural language processing (NLP), in interest assessment. This paper explores the extent to which natural language on social media can be used to predict individuals’ self-ratings on eight basic interests representing the SETPOINT model: Agriculture, Engineering, Human Resources, Life Science, Management/Administration, Mechanics/Electronics, Media, and Social Science. Leveraging closed- (Linguistic Inquiry and Word Count; LIWC) and open-vocabulary NLP approaches (Latent Dirichlet allocation (LDA) topic modeling), we analyzed 3.2 million Facebook posts from 2,834 participants who completed a 32-item basic interest measure. We found that the convergent validities of these NLP approaches for predicting vocational interest scores (LIWC: [Formula: see text] = 0.19; LDA topic modeling: [Formula: see text] = 0.24) are comparable to prior research on language-based personality assessments. Our study also revealed largely face-valid language markers that characterize different basic interests. Implications for developing language-based interest assessments for applied settings (e.g., career guidance and employee selection) and future research directions are discussed.

Presentation of national identity on social media in times of crises: The case of a Palestinian anti-violence movement in Israel

This case study offers an understanding of the perception and use of social media among social activists as means of collective identity formation. It focuses on the case of a Palestinian anti-violence movement in Israel. To learn about the identity presented by the United Fahmawi movement, interviews with two of the movement’s leaders and its Facebook posts were analyzed. The findings show a multi-layered, complex identity. The identity is presented as Palestinian, mainly centered around the city of Umm al-Fahm. Otherness is a crucial aspect of this identity, as Palestinian identity stands in opposition to the Israeli one. Furthermore, the police are presented as the source of the crime crisis, while also seen as responsible for reducing it. This study shows how indigenous social activists use the intersectionality between the social, the political, and the national to present an identity.

Using social media to share universal messages about early language and literacy development with parents and caregivers

Purpose Health promotion and prevention interventions to support children’s early language and literacy development are essential, however little is known about how social media can be used in this context. This study evaluated an intervention which aimed to build capacity of parents in supporting children’s language and literacy skills, implemented using Facebook. Method A cross-sector partnership of Australian speech-language pathologists developed a suite of universal messages for parents to support their child’s language development. Messages were delivered across 12 weeks via Facebook. A convergent mixed methods study design was used to evaluate survey responses from parents of children aged 0–5 years, before (n = 136) and after the intervention (n = 61). Social media analytics were collected. Result Participants identified social media was a helpful way to receive information about supporting their child’s language and literacy development, reporting an increase in knowledge following the intervention. Participants reported they trusted information provided in Facebook posts as it was from professionals and evidence-based sources. The usability (i.e. look and layout) was generally rated highly. Conclusion Social media is a valuable tool for speech-language pathologists to deliver universal messages. Future social media initiatives should be co-designed with families and social media professionals to ensure delivery of trusted, consistent, and user-friendly information.

From facebook posts to news headlines: using transformer models to predict post-disaster impact on mass media content

From facebook posts to news headlines: using transformer models to predict post-disaster impact on mass media content