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多彩贵州宣传文化云创建微博

萌宠菠菠乐园
2024-10-20 13:26

获取多彩贵州宣传文化云创建微博数据

Tweets das Eleições 2018 no Brasil

Tweets following the coronavirus hashtag on 5-6 Feb 2020

Survey data: health information encountered by social media users in their 20s and the factors (environmental, personal, network) that affect these encounters

War Discussion data from a Russian-based social media platform VK

**Museum of Ice Cream** **Official Website:** https://www.museumoficecream.com/singapore **Google Maps:** https://g.co/kgs/qaiHdu **Instagram:** https://www.instagram.com/museumoficecreamsg/ **TikTok:** https://www.tiktok.com/@museumoficecreamsg **Facebook:** https://www.facebook.com/museumoficecreamsg [Museum Of Ice Cream](https://scaniver.se/L1.30251,103.81286) Source: Objaverse 1.0 / Sketchfab

Dataset of all the tweets posted on Twitter(now X) during the "Me Too" Movement

Welcome to the Open Weiboscope Data Access website. Weiboscope is a data collection and visualization project developed by the research team at the Journalism and Media Studies Centre, The University of Hong Kong (JMSC). One of the objectives of the project is to make censored Sina Weibo posts of a selected group of Chinese microbloggers publicly accessible, which enables academic use of the data for better understanding of the social media in China and making the Chinese media system more transparent. Since January 2011, the project has been regularly sampling timelines of more than 350,000 Chinese microbloggers who have more than 1,000 followers. The methodology has been detailed in an IEEE Internet Computing article (Fu, Chan, Chau, 2013). Besides, we have sampled Sina Weibo accounts randomly since 2012 and the samples' most recent timeline were collected and stored into the dataset. Our sampling approach is reported in a PLOS ONE article (Fu, Chau, 2013). This site contains all the Weiboscope data collected in the year 2012. We are delighted to share the data for open access. But for ethical reason, the data are anonymized, i.e. real user and message id are replaced by pseudo ID. When using the data, please cite the paper below. King-wa Fu, CH Chan, Michael Chau. Assessing Censorship on Microblogs in China: Discriminatory Keyword Analysis and Impact Evaluation of the 'Real Name Registration' Policy. IEEE Internet Computing. 2013; 17(3): 42-50. http://doi.ieeecomputersociety.org/10.1109/MIC.2013.28 Data Set Statistics: Number of weibo messages: 226841122 Number of deleted messages: 10865955 Number of censored ('Permission Denied') messages: 86083 Number of unique weibo users: 14387628 Enquiry: Send your question/comment to weiboscope@gmail.com. The project is funded by the University of Hong Kong Seed Funding Program for Basic Research. Citation:Fu KW, Chan CH, Chau M. Assessing Censorship on Microblogs in China: Discriminatory Keyword Analysis and the Real-Name Registration Policy. Internet Computing, IEEE. 2013; 17(3): 42-50.

Unleashing the Power of 3 Million Labelled Tweets for Sentiment Analysis

Amidst infectious disease outbreaks, such as COVID-19, social media is being used to strategically communicate throughout the progression of a public health crisis. The Crisis and Emergency Risk Communication (CERC) Model combines notions of crisis, risk, and outbreak communication throughout different stages of a crisis (Lwin et al., 2018; Reynolds, 2002; Reynolds & Seeger, 2005). This research investigates the ability to adapt the CERC Model to visual outbreak-related updates on Instagram. Instagram posts were collected from a state-level public health authority from March to December 2020 and analysed using a dual qualitative visual and textual analysis. Results suggested that Instagram was strategically used by public health authorities by integrating data visualizations into outbreak-related updates. Additionally, findings indicate that Instagram provides meaningful opportunities for health authorities to engage with their audiences during a public health crisis but underscores the importance of prompt engagement. Publics predominantly engaged in comments expressing shared citizen responsibility for slowing the spread, but the uncertainty associated with this crisis yielded several questions from the public where all inquiry comments were addressed by conspiratorial comments, rather than the public health authority. Limitations and future directions for applying the CERC Model to outbreak-related updates on Instagram are also discussed.

7.6 million Reddit comments between 01/01 - 07/01 2019

Analysis of gender and social media

Ten million answers and their /r/AskReddit questions

This survey charted the gambling, social media usage and subjective well-being of young people aged 15-30 years in Finland. The study was conducted as part of the "Problem Gambling and Social Media: Social Psychological Study on Youth Behavior in Online Gaming Communities" research project. The aim of the project was to analyse how young social media users assess, adopt and share gambling-related online content and how online group processes affect their gambling and gambling-related attitudes. The project was funded by the Finnish Foundation for Alcohol Studies (2017-2019). This dataset contains additional data collected from popular Finnish social media sites. First, the respondents were asked which social media services they used (e.g. Facebook, YouTube, Instagram, discussion forums, online casinos) and how often. Topics that the respondents discussed on gambling-related social media were charted more closely, and they were asked, for example, whether the discussion usually related to instructions or tips on gambling or to problem gambling and recovering from problem gambling. Some questions on the respondents' social media activity were also presented, for instance, how often they saw gambling-related advertising online, how often they changed their most important social media passwords, and how often they uploaded pictures of themselves on social media. The respondents were asked whether they had ever been harassed online or had been the victim of a crime on the Internet in the past three years (e.g. defamation, identity theft, fraud, sexual harassment). The respondents' identity bubbles on social media were surveyed by using the IBR scale (Identity Bubble Reinforcement Scale). The respondents were asked, for instance, whether they thought they could be themselves on social media and whether they only interacted with people similar to them on social media. Additionally, the CIUS scale (Compulsive Internet Use) was used to examine problems related to Internet use. Questions focused on, for example, whether the respondents found it difficult to stop using the Internet when they were online, whether people close to them said they should use the Internet less, and whether they felt restless, frustrated or irritated when they couldn't use the Internet. In the next section of the questionnaire, the respondents were randomly assigned to two groups for a vignette experiment. Respondents in the test group were told they belong to Group C because they had answered the earlier questions in a similar manner to others in the group. Those in the control group were given no information on the group. The respondents were presented with different gambling-related social media scenarios, and they were asked to evaluate the contents of the gambling-related messages by "liking" or "disliking" the message or by not reacting to it at all. Each respondent was shown four different gambling messages with different contents. Three factors were manipulated in the scenarios (2x2x2 design): expressed stance of the message on gambling (positive or negative), narrative perspective of the message (experience-driven first-person narration or fact-driven third-person narration) and majority opinion of other respondents on the message (positively or negatively biased distribution of likes or dislikes). For Group C, the majority opinion was seemingly provided by other Group C members, whereas for the control group the majority opinion was seemingly provided by other respondents. Additionally, the respondents' attitudes towards the message were surveyed with statements regarding, for instance, how likely they would find the message interesting or share it on social media. Next, the respondents' attitudes towards gambling were charted by using the ATGS scale (Attitudes Towards Gambling Scale). They were asked, for example, whether people should have the right to gamble whenever they want, whether most people who gamble do so sensibly and whether it would be better if gambling was banned altogether. The respondents' gambling habits were examined by using the SOGS scale (South Oaks Gambling Screen), and they were asked, for instance, which types of gambling they had done in the past 12 months (played slot machines, visited an online casino, bet on lotteries etc.), whether the people close to them had gambling problems, and whether they had borrowed money to gamble or to pay gambling debts. In addition, the respondents' alcohol consumption was surveyed with a few questions from the AUDITC scale (The Alcohol Use Disorders Identification Test), and they were asked whether they had used various drugs for recreational purposes (e.g. cannabis, LSD, amphetamine, opioids). The respondents' subjective well-being and social relationships were examined next. The respondents were asked how happy they were in general and how satisfied they were with their financial circumstances and life in general. They were also asked how well the single statement "I have high self-esteem" from the SISE scale (Single-item Self-esteem Scale) described them. The three statements on lacking companionship, feeling left out and feeling isolated from the LONE scale (Three-item Loneliness Scale) were also included in the survey. Feelings of belonging to different groups or communities (e.g. family, friends, neighbourhood, parish/religious community) were charted, and the 12-item GHQ scale (General Health Questionnaire) was used to survey the respondents' recent mental health. Questions included, for example, whether the respondents had been able to concentrate on what they were doing, had felt they couldn't overcome their difficulties, and had been losing confidence in themselves. Finally, the respondents' sense of control over the events in their lives was examined with the MASTERY scale (Sense of Mastery Scale), with questions focusing on, for instance, whether they thought they had little control over the things that happen to them and whether they often felt helpless in dealing with the problems of life. The respondents' impulsivity was surveyed by using the EIS scale (Eysenck Impulsivity Scale) and their willingness to delay gratification was surveyed with the GRATIF scale (Delay of Gratification). Background variables included the respondent's gender, age, country of birth (own and parents') level of education, type of municipality of residence, number of inhabitants in municipality of residence, household composition, disposable income, possible financial problems, and economic activity and occupational status.

Top 100 influencers of most countries on instagram,youtube, tiktok and Thread

Transcript of Lex Fridman Podcast #383

30000 post titles from r/AskReddit

This data summarized total numbers of social media platform that utilized by FUTUNE GLOBAL 500 organization.

TGDataset is a collection of 120,979 public Telegram channels, for a total of 498,320,597 messages. The Telegram channels are stored in (alphabetically sorted) 121 JSON files divided in 4 folders: TGDataset_1 -> channels with username starting with A to freeJul TGDataset_2 -> channels with username starting with freejur to NaturKind TGDataset_3 -> channels with username starting with Naturmedi to theslog TGDataset_4 -> the remaining channels

An online survey was conducted from January 8 to March 14, 2024, employing a questionnaire created with Google Forms to assess users' attitudes toward digital influencers and the impact of social media advertising on consumer buying behavior. The survey link was distributed via email and social media to partner organizations, resulting in 376 complete responses during the study period. Various classical and modern statistical methods were utilized to visualize and analyze the collected dataset. Participants evaluated their social media experience based on criteria such as convenience, interactivity, attractiveness, expertise, and trustworthiness. However, respondents' opinions suggest that there is no statistically significant effect of social media influencers on customer purchase intention.