Twitter - Science topic

Snapshot: Moment at 26 seconds in Gavin self-narrating video,

Maintaining a Parkinsonian Narrow Corridor perception.

Please observe that although Gavin is able to move partially from the Parkinson's motor circuity of Festination/Freezing, he is unable to exhibit a more 'skilled' posture of flexing one hip/thigh on the pelvis (literally skipping).

Instead, Gavin maintains a Parkinsonian Narrow Corridor perception.

You can download data with FollowersAnalysis (https://www.followersanalysis.com/old-tweets)

They help you download specific types of tweets you’re looking for, you can Download old tweets related to any hashtag or keyword in a CSV/Excel file for any date range.

You can download data with FollowersAnalysis (https://www.followersanalysis.com/old-tweets)

They help you download specific types of tweets you’re looking for, you can Download old tweets related to any hashtag or keyword in a CSV/Excel file for any date range.

Thanks for this highly relevant question about the relevance of Chatgpt (https.//chat.openai.com ) and similar new AI tools. I have been thinking about it a lot since it was published in its present form a couple of weeks ago. Some unsorted ideas:

In short; with AIs of this and future improved AI versions and information interfaces, information friction has become very low. This is what "digitalisation" has been all about so far in education (to deliver content more easily), when most other fields of activity in society uses also information processing (outside biological brains)- which has hardly begun in education yet. But now it does. We have not seen much digitalisation of education yet. But now it really begins. So we will have a lot of new "blends" between older and newer practices in education.

Try FollowerAudit. It doesn't tell you the bots but can tell you fake, inactive and active followers of a Twitter account.

Twitter provides access to your old tweets and performance metrics, but it’s not the same for other Twitter profiles. You cannot download old tweets of other users directly from Twitter’s official website.

You will have to use Twitter API to gain access to this data. Although, downloading old tweets using the Twitter API requires coding experience. If you don’t have the required expertise or the resources to overcome that, you should use a third-party analytics tool such as FollowersAnalysis (https://www.followersanalysis.com/blog/download-old-tweets/). It allows you to download old tweets related to any hashtags, keywords, @mention, or even tweets posted by a specific account.

Fermented foods and probiotics can have anti-inflammatory and anti-pathogenic effects, a vitamin C deficiency can therefore lead to impaired immune function and a higher susceptibility to infections, Vitamin D supplementation can protect your respiratory tract. Studies show that people with optimal vitamin D concentrations are less likely to experience the common cold and other respiratory tract infections than those with low vitamin D. Ginseng is a root with potent antioxidant effects that contribute to reduced inflammation, support immunity, and other health benefits and Garlic can activate immunity-related genes and lower your likelihood of getting sick ....

I suggest you look at kaggle, e.g., https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset and https://www.kaggle.com/c/fakenewskdd2020 etc.

Hello Maria, hard to answer without more details, so here are some points that may or not be relevant to your purpose.

Try to be outside the scope of GDPR: for instance you can rid off of users IDs by replacing them by hashes. Hashes are irreversible (except maybe agains brute-force attack, but this is any way acceptable by GDPR) and you have a high probability to preserve the association between messages issued by the same person (this is an example of anonymization, which is stronger than pseudonymisation. However, GDPR requires only pseudonymisation).

A possible issue is that a message could contain personal information, like a phone number, political affiliations, etc. However, aggregated data do not fall under the scope of application of GDPR. For instance, if you are interested in sentiment analysis, chances are that you will use a representation such as BoWs (bag of words). A BoW is a way of extracting features from text, and you probably do some aggregations on related terms, so it may be considered as aggregated data (well, it is a little bit questionable...). If your are using Ngrams, you preserve the sequence of words, and it is more difficult to consider some form of aggregation. Depending on your use case, you may have an option to store data in a representation that does not fall under GDPR. It is worth double checking! otherwise you will have many obligations towards data subjects (people who write or are referenced in messages). You will find more details in Art. 89 GDPR (https://gdpr-info.eu/art-89-gdpr/). You may also be interested In the fine for NGO using tweets for a study.

Abiola Olayinka Fafolahan just be wary of what happens to Twitter data when it is viewed outside of the Twitter display:

DiscoverText is not open source, but it is free for academics.

Very useful website reports on Twitter Thought Police termination of accounts.

A. Greede Thank you for your comments. However, it is difficult to confirm whether people in a certain country have adequate security (or freedom of speech).

Happy World Emoji Day, every🧐ne!

Here is a discussion I created about a specific topic:

Please visit that. Thanks

@Luigi Arminio,

This attached screenshot maybe useful. Thanks~PB

I suggest you give the participants an incentive or prize along with these recommendations:

1. Ask your friends who have similar audiences to post on their social media profiles as well.

2. Share the link on active Facebook groups

3.Personalize the communication with the participants

Hi José Wilian Batista Corrêa Several social networks (e.g. Instagram) usually adds some georeference information to posts/photos etc. that can be retrieved with Python APIs. Please consider that retreving these types of data currently violates TOS (terms of use) in most cases. For an example please see our paper regarding influencers on Instagram for sustainable tourism

Email: mdredze@cs.jhu.edu ro4 the paper from 2015

This is the next: Although we have to be careful to make sure all appropriate steps are followed, we are very eager to share this resource with other researchers! Please send requests for access to the dataset to Philip Resnik (resnik@umd.edu). Requests should be based on this sample application, which has two parts:

The involvement scale is adopted from the involvement consumer involvement profile (CIP) scale, the personal involvement inventory (PII) scale (Laurent and Kapferer, 1985; Zaichkowsky, 1994), which outlines 6 items including importance, value, interest, and information. Attitude measurement is adopted from Huang et al.

Media use in minority languages is affected by the position of the language in a growing digital market. ... The asymmetric position of minority languages makes them particularly vulnerable to unfavourable changes in the media landscape. Internet-based and mobile digital media are likely to introduce such changes.

In order to construct a coherent framework, it is crucial to be aware of the philosophical, theoretical and methodological differences and similarities among the approaches. Obviously, this requires an overview of the field.

Reading this article may give you a global idea of how to do it.

Hello Naveen,

This paper might be useful. They have collected Twitter data using Gnip.

FollowersAnalysis(https://www.followersanalysis.com/), a Twitter analytics tool that can help you easily get access to the followers' list of any public Twitter account. Furthermore, it also analyzes your followers and provides comprehensive analytics reports.

While the native download options do provide access to the followers' list, they are nowhere close to the number of analytics insights that FollowersAnalysis provides. These insights can help you make data-driven decisions that can develop effective strategies to boost your social media presence.

This is a disturbing question. If you added the parenthesis (with permission) it might be marginally less so.

Although fb /Meta does use analytic data (and algorithms) to drive their ad delivery, they are reducing the availabilty of that data. Even anonymous demographics about page visitors.

I, for one, would never take part in a study that made giving the researchers the authority to monitor my conversations and reactions on Facebook or similar. And would not answer surveys that would 'validate' my responses in such a way.

In my experience the best way to test responses in surveys is to recast questions so that they appear to be different, but when the responses are compared inconsistencies (fibs?) are revealed. That is, I will ask apparently different questions within the mix of questions in the survey, but some of the key questions are effectively and unobviously asked multiple times.

Research assistants are good yardsticks for this. If they don't see the similarities in the questions, but see them clearly in the responses, you've hit the target.

Dear Souvik Panda

The tool is already available here, but it has faced some problems recently.

It sounds like they have published their items, so you can use them in your research. But be sure to reverse some of the items in the first scale. As for the second scale, it seems to be a real mix of content, from disliking fake news to creating it.

What do you mean by a "dimension less" Likert scale?

FollowersAnalysis is a Twitter analytics tool that offers a comprehensive analysis of tweets and followers along with the actual data.

You’ll have access to tweet specifics, as well as detailed analytical data. The tweet analysis report includes an analysis of the user’s tweets.

Dear Tamara,

In some of my publications, I have described the process of adjusting the standards for the functioning of market structures, legal norms, the structure and operation of individual markets, industries and sectors of the economy, including adjusting the domestic financial system to the standards of the European Union. I have described the issues of adjustment processes to EU standards on the example of the country in which I operate. The aforementioned adaptation process began with the socio-economic changes in 1989, i.e. right after the system transformation. I studied the aforementioned adjustment process mainly on the example of the domestic banking system, which since the beginning of the 1990s was adjusted to the standards of functioning of banking and financial systems in the EU. Thanks to the conducted adjustment processes, the country was able to enter the structure of common EU markets, which happened in 2004. Thanks to these adjustment processes, the functioning of the domestic banking system was significantly modernized. The aforementioned adjustment process is also interpreted as an important factor in accelerating the processes of globalization of financial markets, a factor in increasing the standardization and unification of financial systems. I have described these issues in several of my articles and chapters of academic textbooks that are posted on my Research Gate profile.

Best regards,

Dariusz

Hadeel Almasaid Twitter provides free access for academic purposes, but you have to apply for a key and token first:

Once you have this information, you can then use their API to download the data you are interested in:

Do you want to get a list of Twitter followers of any public Twitter account?

FollowersAnalysis a Twitter analytics tool can help you easily get access to the followers' list of any public Twitter account. Furthermore, it also analyzes your followers and provides comprehensive analytics reports.

While the native download options do provide access to the followers' list, they are nowhere close to the number of analytics insights that FollowersAnalysis provides. These insights can help you make data-driven decisions that can develop effective strategies to boost your social media presence.

All qualitative data analysis (QDA) software packages do almost the same thing. Therefore, the one you should go for is the one you are familiar with. If you consider spending time getting the grasp of a new QDA software, you might opt for MAXQDA for its functionality and tutorship. The comparison by the NYU Libraries (2021), referenced below, could come in handy.

NYU Libraries. (2021, November 11). Research guides: Qualitative data analysis: Choosing QDA software. Research Guides at New York University. https://guides.nyu.edu/QDA/comparison

Good luck,

Dear Asma Siagh

The significance of pretrained word embeddings was highlighted, as well as two prominent pretrained word embeddings - Word2Vec and gloVe.

This article seems to be useful, have a look:

Best Regards

Depends on library function used to manage twitter api. Tweepy doesnt support location.

You may submit it in some facebook groups.

Hello

First, you could do a bibliometrics analysis. It opens windows. By this analysis, you can find important information about.

Best regards

This is a very interesting topic of study. I have some books on translation I'll see into them if any of use to you I'll let you know

Joao Luiz Junho Pereira I don't think the journal you proposed is suitable for what Reem Ml is looking for. In fact the question was about a journal related to Twitter Arabic Sentiment Analysis to Detect Depression Using Machine Learning so it preferred to have a journal that deals with Machine Learning, Artificial Intelligence such as:

- Machine Learning with Applications not impacted but indexed (https://www.journals.elsevier.com/machine-learning-with-applications)

- https://www.journals.elsevier.com/expert-systems-with-applications

- https://www.journals.elsevier.com/artificial-intelligence

- https://www.journals.elsevier.com/engineering-applications-of-artificial-intelligence

- https://www.springer.com/journal/10994

Hi Almas Shabbir

Check out the following link and the links in the description.

Basically it is possible. But I would say the data may not be representative and/or accurate. False information result in false predictions and wrong conclusions. As you may know, the first step in doing so, is making sure you have clean data. It is difficult to do this I believe. Not only for the source of information, but also because of the psychological parameters that are involved.

Julie Eshleman

The use of the word "realist" assumes a significant bias on the part of the user of a methodology. A preferable approach would be phenomenological, where individual realities are systematized. Care for individuals requires understanding of individuals.

Sincerely, Kurt

A Supervolcano is a term that refers to a type of volcano that has a magma chamber that is a thousand times larger than that of a conventional volcano and therefore has the largest and most voluminous eruptions on Earth.

Yes, you can use this data but this data much be authentic and you need to give citation of that specific data in your research as well. That data need to be selected via certain sampling technique and much be sufficient to fulfill your objectives and answer your research questions.

First of all, you have to decide what your requirements are. Do you want a disorganized list of tweets or an insightful report of tweets with comprehensive analytical insights? Both include tweets however, an analytical approach of the same can be beneficial for research work and analysis.

FollowersAnalysis (http://www.followersanalysis.com/) is a tool to analyze comprehensive data of Twitter accounts. Apart from tweet details, tweet analysis is also accessible when you download it from them. This tweet analysis report includes the most recent 3200 recent tweets of the user. The comprehensive data you get in the report is precise and accurate.

https://storywrangling.org/about I believe storywrangler is the right way. At the Computational Story Lab, since 2008 they have collected a random 10% of all public messages using Twitter’s Decahose API. Overall, the collection comprises roughly 150 billion messages requiring 100TB of storage.

Inspired by the Google n-grams project which smashes books into bits, we’ve meticulously parsed these tweets into daily frequencies of words, 2-word phrases, and three word expressions. Scientists call these different types “n-grams” for n = 1, 2, 3.

thank you

https://www.mdpi.com › pdfPDF

Sentimental Analysis of COVID-19 Tweets Using Deep ... - MDPI

Ismail Shaheer thanks for all the efforts, i am looking for some personal recommendations and tips regarding twitter as a tool in medicine / dentistry.

You can visit https://www.followersanalysis.com/

Currently, the best way to get this data is to contact them with your requirements at contact@followersanalysis.com or use the chat option at the bottom right corner of their site and they will be glad to assist.

I think, it is very common issue in every country.

Python has a lot more features. I think no one knows 100% of python. From your brief, it seems like you need someone who knows Python AI and ML.

You can find a python specialist from:

(2) https://www.toptal.com/python

(1) https://www.codementor.io/python-experts

Hi Mark de Kwaasteniet , thanks for sharing your thoughts. My answer is: Yes it is sensible to use control variables in your VAR model. Why some studies do not use control variables is very hard to say. It depends on the nature, background and purpose of some reserach. May be this will be of help: ECONOMETRICS MEETS SENTIMENT: AN OVERVIEW OF METHODOLOGY AND APPLICATIONS

Andres Algaba, David Ardia, Keven Bluteau, Samuel Borms, Kris Boudt

First published: 21 May 2020, https://doi.org/10.1111/joes.12370. KR Rob

Hi Oscar,

You can use Trackmyhashtag to download old Tweets. It is a Twitter analytics tool that can track any hashtags or topic and provides useful detailed analytics in real-time as well as historical.

It can help you to download old Tweets of any user since 2006. You will get complete tweet detail including total tweets, tweet content, contributors detail who contributed to that specific tweet, and other lots of useful metrics.

You need to visit this page: https://www.trackmyhashtag.com/historical-twitter-data

Here you will find a "Request data" form which you have to fill with your search term and select the dates and submit. After a while, you'll receive your Tweets data and other details with it.

Thank you:)

Interesting topic.

Interesting topic.

You could go for content analysis (i.e., counting codes). You could do:

codes counting > pattern matching > cross-case synthesis.

You might have a look at the insights by Stake (2006), referenced below.

Stake, R. E. (2006). Multiple case study analysis. The Guilford Press.

Good luck,

Scraping Twitter data and analyzing it can help get access to valuable insights that can enhance your marketing strategy.

FollowersAnalysis, (https://www.followersanalysis.com/) an amazing Twitter analytics tool that can help you extract tweets related to any @username or targeted keywords.

Scrape more than past 3200 tweets of your brand’s Twitter profile, competitors, influencer marketing candidates, etc. FollowersAnalysis doesn’t just give you access to Twitter data you also get access to analytical insights and predictive analytics.

FollowersAnalysis can also help you analyze your Twitter followers. Similar to tweet analysis, you get various analytical insights about your followers. You can extract entire lists of Twitter followers and follows in an Excel/CSV file. Identify influencers, most engaging followers, identify the target audience, find inactive followers, and more

· Scrape Twitter data

· Perform tweet analysis

· Analyze Twitter followers and extract data

· Identify influencers

· Identify the most popular tweets and most engaging followers

Lana Jurman I ran into this problem. Later, I started using MAXQDA for this kind of content analysis data. Have you tried this program?

https://www.researchgate.net/post/What-is-the-best-way-to-do-a-sentiment-analysis John Ndavula Already discussed and many experts are replied.. You may get information from here.

Dear Ioanna Anna Papachristou

You can use the "Tweepy library" to extract Twitter data.

To learn how to use Tweepy library in python, check out the following link:

Yes, indeed you may, if that was the method you used.

There will be a few factors to consider:

But in the case where you're able to scrape multiple tweets of an individual with geo-coordinates available, it should be possible to plot all post on a map and trace their footsteps (using simple lines with arrows to link locations timeseries-wise)

Amritha Sasankan good interrogation

I agree with Mohamed Elhadad . First level of differences is the difference in language between or witin regions of the world. Even if you use countries as unit of observation, you will encounter different langauges for some countries. You could try to just filter english tweets from the regions, probably reflecting in a biased sample. Second level are the regional differences you particularly want to account for. Last but not least it is important to note that Twitter "slang" can deviate from regular communication behavior and thus it would be wise to link "real-life" evidence of mental health issues (or indicators) to online behavior. I think this is a really hard job when considering level 1 and 2 and doing it for "all the world". Nevertheless, this paper might answer a part of your question or:

You can go with some indepth interviews (IDI) and one or two focused group discussion (FGD).

Choose the analysis pattern- content or thematic based on your study objectives, type of questionnaire you develop and finally the type of data you will have.

TagPredict. It can be downloaded for free from the Google Webstore and this is how it works:

The main functionality of TagPredict is hashtags scraping. It is very smart and can scrape in two modes: “automatic pilot”, which scrpes everything, or “top 40” mode which scrapes the top 40 popular hashtags. For further details you can check it down from Quora

Mehdi Habibian,

Here you are an advanced Twitter scraping & OSINT tool written in Python that doesn't use Twitter's API, allowing you to scrape a user's followers, following, Tweets, and more while evading most API limitations.

link: https://github.com/twintproject/twint

I hope this could help you and all others who are interested.

Good luck to all of you!!!

Dear Sofia Kolos,

Yes, I use hashtags on such popular social media portals as Instagram, Facebook, Twitter and LinkedIn. however, the use of hashtags is not justified on all types of social media portals. The importance and effectiveness of using hashtags on different types of social media portals is not the same.

Regards,

Dariusz Prokopowicz

You collecting live streaming data from twitter for prediction. But to the train data that needs labeled data what do i do?

Does it have to be all the platforms? Different platforms may pose challenges in your data collection if you plan to collect the social media content (twitter allows automated content mining, facebook is dependent on the privacy settings). I suggest you define your research questions and then choose an appropriate methodology to answer those questions. Good luck on your studies.

If its very short... Maximum 40 -60 seconds.... Michal Kuniecki

Read this article.

Hello!

You may take a look at