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Twitter - Science topic
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Questions related to Twitter
I can teach Gavin (guy in the #Parkinsons self-narrating Twitter video above) how to fall gracefully using my Neuroplasticity, movement-perception method, and then he would feel safe at all times to move in space.
I believe that by listening to people that attempt to articulate for us their fluid condition of Parkinson's, we can make many discoveries and help Mankind.
Hello, I want temporal dataset for twitter for my research for example detect fake news on twitter
I am looking for historical spatial-temporal Twitter datasets. I am familiar with Twitter APIs, but it does not give me what I want. I am searching for a website which has stored spatial-temporal data for a period of time. I am wondering how and where I will be able to find such data.
I would be grateful to hear your kind responses.
Is there any way to reliably identify the gender of the person in Twitter data (which has no gender identifiers)? I'm talking about content in Polish.
Chat GPT, powered by GPT-3 model from OpenAI, has reached 1 million users only in 5 days. Facebook, Netflix, Instagram, and Twitter could reach this number in 300, 1200, 75, and 720 days. Chat GPT can engage in multiple ongoing conversations, understand and respond to natural language input, and offer customized and interactive assistance. This makes Chat GPT a promising tool for students and and naturally universities.
What is your opinion? What Chat GPT Mean for Students and Universities?
I am looking for some programme that allows me to identify bot accounts in the data collected by me.
Is there any tool that can help me download tweets related to any hashtag
I would be most grateful if you kindly answered this question on Twitter for research purposes only between 1-15 Dec.2022! Thanks a million in advance:
We are working on a project with the goal of predicting Fake/Real news on tweet texts, using machine learning and deep neural networks. but the basic and maybe the most important obstacle is the first one, Train/Test Data.
Does anybody know an annotated dataset in persian tweets for this task?
Thanks for your ongoing replies dears!
I am interested in the interactional aspects of Twitter, that is how people reply to one another. I have tried Netlytic, but it doesn't scrape the whole conversation but only the tweet that is a reply to another tweet, without collecting also the tweet that originated the reply/ies.
Is there a software, out there, that collects all the tweets in a discussion, starting from a search word/string?
Could that be retrieved with python on the Twitter API? How?
I am doing my research in hashtag activism. For that I need to collect twitter and facebook data. Which software can help me in doing data collection and analysis? I have tried nvivo n capture. What are the other suggestions? Kindly help Thanks in advance
My account at Twitter has been suspended because I shared official US Government information, posted by another user that I found when searching on a topic.
I was not given the option of hiding or even deleting the item, which showed a case reported to VAERS of a young child who died during a COVID19 vaccine trial.
The record contained clinical information that suggests it was lodged by a medical professional.
I would be interested to hear from other researchers who have had their social media accounts locked, suspended or terminated.
On social media platforms (e.g. Twitter), after posting a tweet that has been used to refute false information, is it reliable to use the comments below it to assess the credibility of the tweet? As it is the user's choice whether or not to comment, does this practice lead to selection bias? For example, under the pressure of certain social norms, it takes courage to refute information posted by an official account, i.e. users who support the official claim are more likely to comment.
There is a new interface needs to review from Twitter.Are there any other way to get that? Thanks
We use intonation or facial expression while we are talking to each other. But, in the case of posting short texts, the story is different. Online users used to use emoticons ;-))) After a while, tele-communication companies started introducing picto-graphics called "Emoji " which are very popular these days. People use them in short texts they send or post because they are useful in conveying users’ feelings. Despite their wide use, we still do not understand the patterns in their usage.
Is it possible to claim that emoji is a new set of symbols forming a language? If yes, can we show this language can reflect the feelings better than the other traditional languages?
How can scientific discussions and collaboration be more alive? No-one is responding to anyone else. Would it be a nice idea to create a twitter discussion or Facebook group?
I'm looking for datasets containing coherent sets of tweets related to Covid-19 (for example, collected within a certain time period according to certain keywords or hashtags), containing labels according to the fact they contain fake/real news, or according to they fact they contain pro-vax / anti-vax information. Possibly, the dataset I'm looking for would also contain a column showing the textual content of each tweet, a row showing the date, and columns showing 1)The username /id of the autohor; 2)The username/id of the people who retweeted the tweet.
Do you know any dataset with these features?
My questionnaire was distributed via online through the SABPP, to a target population of over 8000 members. After a week I only received 17 responses. The questionnaire link was placed on Instagram and Twitter, which increase the responses to a total of 25. What can I do?
I'm trying to analyze some publications on social networks in order to map publications that report urban problems and, thus, analyze urban areas that are affected by similar problems.
Can you help me to obtain the data set of these links. Thank you so much.
4.3 Twitter Datasets Collection
I am currently researching about impact of customer involvement through social media or other web platforms on product innovation. While for product innovation I want to use patents to measure product innovation performance, I am a bit lost how to measure customer involvement (without a survey). I was thinking about different social media platform e.g., Twitter but I am afraid there is too much unrelated information if I am searching for specific products via hastags or a text query.
In addition, have you stumbled across cool & interesting moderators that are easy to measure?
We are conducting a research about the language use of Manobo students on social media specifically facebook, twitter and instagram. Your input could surely enhance the said endeavor.
Thank you very much!
I wanted to do a discourse analysis of the text on Twitter, but the data was too large and I had to determine a small range, so I did a random sampling. But the data is still too big. Can I do a word frequency count on the sampled data to find the most frequent words and then randomly select the samples for analysis in details?
I am planning to start an experimental study where I use social media posts as tweets and Facebook posts to ask Turkers if they believe the information posted in there or not. I will be manipulating some parts of the posts (i.e. the text, the URL, the image etc).
I plan to study the impact of these different elements of posts on the perceived credibility of health information (I establish factual truth of messages separately based on scientific evidence). Since asking people what elements of a tweet make a message more or less credible for them might not result in reliable answers (people might not know/ not be aware/ be biased by priming).
I have couple of questions regarding this study:
1- Ethical concerns: can I manipulate the tweets/facebook post before showing it to Turkers? Do I need a consent form from the users who posted these messages since I will be using their original text.
2- do I need to show the whole post as it is, I mean, I have seen studies were they just show the text without the frame or logo etc.
I would very much appreciate it if I can get references that explain how to do this the proper way. this is my first time doing an experimental study. I plan to do a pre and a post survey with the experiment. so any feedback/guideline would be very helpful.
Hii, I decided to do a project on social sentiment analysis for predicting cyber attacks in twitter. So I need to collect data from twitter for training and testing the model but it's my first time and i don't have any experience. Can you suggest me a free and easy way to collect the data without the need for much technical and coding knowledge.
I'm currently trying to use Twitter as to collect data for my research project on the use of AAVE by white gay males, but I have to admit, I find it very hard to navigate the API. Does anybody know how to search the accounts of a selected number of users for a set of specific features? Ideally, I wouldn't look through the accounts one by one, one select feature after the other, but all at once - but I don't know if and how that is possible. I've tried using R with a bunch of extra packages, but since I have no coding experience, this is all very confusing to me.
Thank you in advance!
Is it possible in any way to obtain in an automated way the activity logs data from an individual FB user? For example, with the use of some API or analytic tool?
I'd like to compare the data from a person's psychological questionnaires with that person's activity on FB. Are there any tools to obtain the latter?
I want to know is it possible to collect Twitter data using twint library and if possible then please give me details of the process.
Hello, I have a question regarding an investigation of Reuter et al. (2019)
Where I have managed to extract the questions (5 scale likert) that I detail below
- Fake news poses a threat
- Fake news can manipulate the population's opinion
- It's the task of the operators of Facebook, Twitter and Co. to prevent fake news
- Fake news can manipulate the opinion of politicians, journalists and other influential players
- Fake news harms the democracy
- It's the state's task to prevent fake news
- Social bots pose a threat
- The state censorship poses a threat
- Fake news is just a pretext to be able to fight system critical actors
- Fake news is at most annoying, but does not pose a threat
- I have perceived fake news
- I have deleted/reported fake news
- I have dislikes fake news
- I have commented on fake news
- I have liked/disliked fake news
- I have shared fake news
- I have created fake news
Since this research has not named its questionnaire and it does not yet have dimensions. Can I take it as a reference in my research?
Of course, the issue later will be validation and reliability. Can you please guide me if there is already a defined questionnaire for these variables (attitude, interaction)?
As Twitter Streaming API provides only 7 days past tweets.
I guess that my question is one in a million, but I am looking to feed my Feedly (and my research as a result). I am interested in several domains and subdomains and thus looking for the best journals / newspapers/ magazines/ blogs/twitter profiles/twitter hashtags on :
1 International relations, in general, but also :
- US foreign policy,
- African news,
2. EU Regional Policy, in general, but also :
- EU territorial cooperation
- EU urban policy
- Multilevelgovernance, europeanisation
Thus, please do not hesitate to recommend any point of information you deem worth of interest or even your own profiles.
Thank you very much in advance!
Can we collect tweets entail a certain language style of a public figure? such as offensive tweets of someone...
I'm searching a database containing statistics on companies' followers, likes, tweets on Facebook, Twitter and/or Linkedin?
I've got a bunch of Twitter data to code, and want to know what researchers feel are the most effective qualitative data analysis apps/programs. The data are in xlsx format.
NVivo looks not so great, and looks to work better if using NCapture from the outset.
Any other good alternatives out there?
I have a multilingual Twitter dataset (Arabic, French, and English), and I would like to use pre-trained word embedding different from gloVe because of the small data size.
My questions are:
- Where could I find multilingual pre-trained wor2vec embeddings?
- Could I combine different embeddings of different languages?
I want to prepare a dataset where the instances would be the tweets from Twitter (will be collected through Twitter API). I want topic-related tweets in one column, the time when it was created in another column, the id or user name of it in another, the location from where the tweet was generated (nominal location, e.g. city or state) in another column.
Thanks in advance.
I was hoping to get some advice regarding recruitment tactics for sensitive populations. I have received ethical approval for recruitment via social media platforms. So far, I have used Reddit, Facebook, Instagram and Twitter, and still struggling to get appropriate numbers for my target population. I would greatly appreciate any advice.
My study titled 'The Parenthood Trap: Conflict, Dispute & Sexual Control in Romantic Relationships', aims to target individuals specifically who have experienced Reproductive Coercion!.
I'm working on my PhD dissertation which focuses on the experience of media journalists on Twitter. Basically, I am going to examine how their production, distribution, and consumption practices have changed in the new media ecology. But I am still undecided over the theoretical framework I should use for the study. I am currently reading on journalists' online experience to see if I can find relevant research.
Do you have any suggestions?
Can you kindly refer me to research carried out on the relation between social media (such as Twitter, Instagram, and Facebook), and translation?
For example: how has the advent of these social media platforms changed the practice of translation in fields such as media?
Thanks in advance.
As said in the title, I'm looking for a journal related to my research Twitter Arabic Sentiment Analysis to Detect Depression Using Machine Learning
to publish it it's preferred to be Q1
please help me out.
I new in python coding. I have a dataset that contains twitter handles of users and there single tweets containing specific keywords. I need to extract each twitter profile information for further processing. I know i can do this using tweepy. But i don't know how can i extract account info of user by using twitter handle. Please help me out.
For my research project I am going to predict dating violence separately using twitter data with a deep learning approach. So I need more information for this purpose.
I am doing a discourse analysis of the content of Twitter, with a total of 200 pieces of data. I set up five questions to ask each content, but not all posts can contain potential answers to five questions at the same time.
Therefore, I would like to collate and analyze the data on questions basis. Is this feasible?
Let me give an example: here are two posts
A：our motherland is very strong
B ：what on earth is the government doing?
My question for these two posts is: what is the imagination of the country reflected in the discourse?
However, the content of B does not seem to deal with the imagination of the country.
So I organized it as:
What kind of national imagination is reflected in the 2 posts?
Embody the individual's imagination and cognition of the strength of the country.
I am a first year PhD student looking to engage with as many different realist researchers as possible as I am trying to make sense of my methodology and methods for my research. I would appreciate any Twitter account recommendations, or any other researchers to follow aside from those in the RAMESES projects (already BRILLIANT materials!). Many thanks in advance for your assistance!
Should we worry more about these Super-Volcanoes like Krakatoa and Yellowstone?
Potential for harm and disaster? Move populations away from the local area?
We sit and wait for disasters- why no forward planning and strategy for mitigating manoeuvres ?
We know enough to identify high-risk areas- why no action?
Our inaction is very disturbing. We are sitting ducks for disaster. Our leaders are not leading. The priorities are wrong.
The warning bells are ringing, but no one is listening
I'm doing a study that needs to compare changes in cyber nationalism.
Can I use the contents posted by people on Twitter for A nationalist incident and the contents posted by people on Facebook for the B nationalist incident to do discourse analysis and compare the changes in nationalist expression?
I'm trying to analyze comments made on Twitter and I need to download about 2,000 tweets.
I would like to see how the time series of a word change on social media (e.g., Twitter)?
Is there something like Google Trends for social media?
I Need research articles in digital marketing of agricultural industries.
How the social media, video marketing, Whats app, Instagram,Twitter & Face book are helping the Agricultural companies in selling their products.
I would appreciate it if you suggest me some public twitter sentiment analysis dataset during COVID-19 pandemic
What are your personal opinion / experiences about tools such Twitter in health care context. Any tips to use twitter more efficiently or evidence based tweeting or live tweeting during conferences?
Inviting stalwarts / bloggers / researchers
for some brainstorming inputs in health care frame work.
I am interested in tracing the way people talk about a specific topic on twitter. I have a set of hashtags, but I am not sure about the best tools to extract the related tweets.
I am looking for a COVID-19 dataset with tweets or text to work on fake news detection. I have found https://www.kungfu.ai/tracking-coronavirus-disinformation-on-twitter/ but was curious if any resource or dataset is available.
Any valid inputs are highly welcome.
We are doing research on a music band and wanted to set up Python or other tools to make research on how people discuss the band on social media, Twitter and other platforms.
I myself in history and don't really know how to do it. maybe there are people in social sciences that used a tool for that?
PhD Candidate, The Graduate Institute, Geneva
Currently i am working on my thesis and i am stuck with the following question. Is it sensible to include control variables in my VAR model?
Right now i am using a VAR model to estimate the effect of Twitter sentiment on European index returns (E.g. DAX). I use both intraday (30/60min) and daily data to estimate the VAR model. However, i am not sure whether i need to include control variables into my VAR model. I was thinking about controlling for inflation, interest rate or GDP, but i have not found any other studies including these variables. Since i am a student i am only capable of finding daily data for the aforementioned control variable, so maybe it is more sensible to leave them out anyway.
Right now i am interested in estimating two VAR models:
1. Sentiment score on Index Returns
2. Tweet Volume on Index Returns
Is anybody able to help me? A link to an article or something else would also be very welcome.
Can anyone help me find a tool that allows me to download the old tweets in the history of a user. I need to study the content of the tweets of 2011 from a group of users who used a # hashtag.
I need the dataset to train a classifier to gather cyber threat tweets.
Good afternoon, need help from Oasys GSA users. I'm not sure what I'm writing in the right place, but I hope there are users who have encountered this. I am a student writing a thesis on "designing a pedestrian bridge using tensegrity structures". In this software package, the process of form finding is quite well performed, and I want to describe it in my work. But I can't find an available version of this program anywhere. My requests on the official website, emails to the mail, as well as on social networks such as youtube and twitter remain unanswered. Although I just need the standard two-week trial that they have to provide. Maybe one of you knows how to reach them?
I am doing a case study research on the operation of cancel culture within the public sphere on Twitter. By looking at three different cases of cancel culture on Twitter, I would like to examine four sub functions of deliberation (one of the key functions of the public sphere) to see if and how there is a connection.
I would like to conduct a quantitative content analysis of twitter threads per case.
What type of statistics tests would be suitable for this type of research?
(the research is more explorative rather than comparative and I don't know yet whether a binary scale or an interval scale would work better for the analysis)
Is there a tool to Scrape Twitter data and perform tweet analysis?
I'm doing a research project, comparing Facebook posts and tweets of a certain politician, using NCapture to capture data and then importing it into NVivo. After some initial difficulties, I've managed to capture the data from Twitter. However, now, no matter how many times I try (even from different Twitter accounts), I am unsuccessful: NCapture claims I have exceeded the limit Twitter allows individuals to make in a 15-minute interval (even in the first attempt, even after waiting for an hour before trying again). Has anyone else encountered this issue?
The study is about political expressions on Twitter and focuses on hashtags that are generated on Twitter.
Does anyone know how to extract all twitter images under a specific hashtag using python or R? Any relevant packages?
PS I am not searching how to extract all images uploaded by a user.
Using set of tweets containing some geocoordinates and some location place id's, what techniques methods can be used to check where do the users go, how much do they move.
Has it increased for all platforms, or do we see increased usage of some platforms while the usage is declining for others?
Enterprise Social Networks (ESNs) are online social networks that are used to share business interests and/or activities among the corporate world. This is similar to the use of Facebook, Instagram, Twitter etc. in our personal lives. Companies implement ESNs to allow smooth communication and collaboration amongst employees or with external stakeholders, information exchange and for updates and tracking.
How can we consider linguistic differences in the analysis of Twitter data?
I'm trying to use tweet data as a proxy for mental health status worldwide. How can I minimize the bias due to linguistic differences as I may miss some data in languages other than English?
I want to study the increasing polarization on social media. I have to use a qualitative method to do so. However, I am more familiar with quantitative methods. Hence, I am struggling to find a way to examine this topic using a qualitative perspective.
Can anyone help me ?
Hello All! I'm currently doing research on my thesis that i have to extract the data from Twitter and Facebook using certain tags? can someone help me how to do this?
I'm searching for relevant studies on 'Linguistics Interference' (interference at a lexical level - borrowed words - grammatical interference in terms of word order, use of pronouns ..etc.).
Linguistics Interference from\between English & Arabic.
I work on Twitter data, I want to extract the user's age. There have been some challenges in the way:
Because I deal with a huge load of data, I can not use age predicting methods to solve this problem also I can not use a Twitter developer (https://developer.twitter.com/en) for this matter.
Do you have any suggestions?
I`m specifically interested in Instagram, Facebook and Twitter.
Where can I find a Twitter dataset for Preliminary Flu Outbreak Prediction Using Twitter Posts Classification?
Hello, I am writing my bachelor's degree and I want to study how a certain party communicates through mass-media (I am most interested in Twitter, Facebook and Youtube).
How should I approach this?
As in the tile - can anyone please direct me to the creditable source/manuscript detailing what is an average time for reading/attending to a single message/post on social media (twitter or facebook) ?
I am working on the stock market price prediction. I have to extract Influential users from the twitter dataset. Is there anyone who can guide me on how to extract Influential users from the twitter dataset?
Please suggest the pertinent R package for analyzing twitter data on hashtags and top trends for specific locality and specific time period. If any one has already work on such type of data then please share the R-codes for understanding.
Thanks in Anticipation