Superb cloud-based software tool with powerful text analytics with social media integration.

Bewertet am 19.12.2017
Wasim A.
Teaching Assistant & Demonstrator
Hochschulbildung
Verwendete die Software für: Mehr als 2 Jahre
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: It allowed me to conduct research that otherwise would not have been possible including both industry and academic projects.

Vorteile: The ability for those from the social sciences to be able to import and/or retrieve social media data, including historical data from Twitter, and analyse the data in order to answer research questions. This is because other tools may require a computer science background. Consequently, DiscoverText has been used in answering important social science questions leading to peer reviewed outputs. Over the years I have seen many tools appear and slowly wither away, however, DiscoverText has stood the test of time and has been growing in popularity. DiscoverText is not limited to academic uses and has a number of neat uses in the commercial world. A useful feature applicable to the commercial domain is the ability to retrieve and/or import data from Twitter and identify influential Twitter users, with the additional ability to use machine learning to sift influential users into different groups. For example, a football club may be interested to find out whether influential users are fans of the club or whether it is opposition fans causing a storm. To the best of my knowledge, no other tool is capable of doing this with this level of accuracy.

Nachteile: To be fair this is not a limitation of DiscoverText per se, as this is a restriction from Twitter, but there is a limit to how many units of tweets can be exported per day. This is not a major issue because there are enough features in DiscoverText that you may not necessarily need to export the data. This is particularly true with a recent integration with NodeXL which provides the ability to export directly to a format supported by NodeXL.

We have been using the software to study twitter conversations on immigration going back to 2013.

Bewertet am 29.1.2018
Jim W.
Director, Center for Social Science Research & Professor of Sociology
Hochschulbildung
Verwendete die Software für: Mehr als 2 Jahre
Quelle des Nutzers 
4/5
Gesamt
3/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
4/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: Easy data capture

Vorteile: It's ability to capture tweets and now the capacity to export to NodeXL gives us two tools that we use together to study the content and structure of immigration conversations onTwitter.

Nachteile: At times navigating the menus is counter-intuitive as is some of the terminology. Archives, buckets, datasets all kind of run into one another.

Antwort des Softwareanbieters

von Texifter an 30.1.2018

Dear Jim,

Thanks for your and the generosity of your Tweets. We really appreciate that!

I'd like the opportunity to visit GMU to make the case that archives, buckets, and datasets are essential parts of the text analytics methods we have engineered. Please email info@texifter.com if you would like to host a free workshop.

Briefly:

- Archives are raw data.
- Buckets are subsets of raw data.
- Datasets are coded by humans.

Most projects proceed from 1 or more archives, to many buckets, to a series of codeable datasets. For example:

- Collect 100,000 #metoo tweets
- Deduplicate the archive
- Create a bucket of seeds and singles
- Search the bucket for key terms
- Create a new bucket with results
- Create a dataset and code it for relevance
- Train a relevance classifier
- Apply the classifier to new archive samples
- Repeat as needed

The key point is that raw data is messy in the archives, cleaner in buckets, and fully refined and classified in datasets.

Twitter and text analysis

Bewertet am 21.4.2019
Demirdis S.
Full Time PhD Student
Hochschulbildung, 5.001-10.000 Mitarbeiter
Verwendete die Software für: 6-12 Monate
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Vorteile: Discovertext provides huge number of filtering options. I am doing a research about Twitter users and my data size is very large. Firstly, Discovertext help me to clean my data by using duplicate and near duplicate functions. Secondly, Coding is very easy by using Discovertext, It is really time saver. I should classify key influencers and most retweeted tweets etc., It has easily done by provided filters. Finally, Discovertext automatically create reports related to results.

Nachteile: Sometimes, I do not understand some filtering options and could not find a information about them but helps always provided by customer support quickly.

Antwort des Softwareanbieters

von Texifter an 26.4.2019

Demirdis,

Thanks for sharing the feedback and we are always happy to sort out anything that might be a challenge.

https://calendly.com/discovertext
https://texifter.zendesk.com/hc/en-us

Good luck with your work!
Thank-you,
~Stu

Great for analyzing social media data- just not offline documents.

Bewertet am 7.4.2018
Katarina A.
Executive MBA Student
Verwendete die Software für: 1-5 Monate
Quelle des Nutzers 
2/5
Gesamt
2/5
Benutzerfreundlichkeit
2/5
Eigenschaften & Funktionalitäten
3/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis

Vorteile: If you need to analyze data from social media and survey monkey- it's a great tool. You can search for content by keywords and the data drops in per the chosen frequency. It breaks down keywords and phrases to a list in order of use- where you can drill into each word or phrase to see where it's used and also toggle between different ways of displaying the results.

Nachteile: I got the trial version to see if it would suit my purpose; I required a tool to analyze and cluster data from articles and other sources but just couldn't get it to work. If the trial period had been longer than 3 days ( I thought I signed up for 30- it's not very clear) I might have had time to figure it out. Better instructions would have helped. The instructions tell you what the features are, not why you need to use them which is not helpful for novice users.

Antwort des Softwareanbieters

von Texifter an 5.9.2018

Katarina,

Sorry for the confusion about the length of the free trial. It was 30-days for many years and we changed it to 3 only recently. Please send a request to info@texifter.com and I will send you a 6-month license.

For details about the features, we suggest you review some of the support materials:

https://texifter.zendesk.com/hc/en-us

As to why use the tools, perhaps review the tutorials:

https://discovertext.com/tutorials/

You might also find some answers as to why use the tools here, in the 200+ academic citations of the tools:

https://discovertext.com/publications/

Finally, I am available for 1-1 web trainings:

https://calendly.com/discovertext

So, I think you may not have fully tried to use all the customer support options. We work very hard to make sure newcomers get comfortable quickly.

Stu

Excellent tool for group coding, text cleaning, deduplication, and training ML models

Bewertet am 24.4.2019
Shawn W.
Assistant Professor
Bildungsmanagement, 5.001-10.000 Mitarbeiter
Verwendete die Software für: Mehr als 2 Jahre
Quelle des Nutzers 
5/5
Gesamt
4/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: I use DiscoverText as a way to introduce my students to qualitative coding at the unit level, data cleaning, and training an ML model. It's a great tool for students without programming experience to work with data. In my own work, I use it to clean, deduplicate, and code social media datasets. The data cleaning and search functions are very powerful. The ML training features are also quite powerful.

Vorteile: The deduplication tools are amazing. Group coding is a snap. So is creating and testing training datasets.

Nachteile: The interface can take a little while to get the hang of -- some of the options are a little hidden, but the support is VERY responsive and the tutorials are helpful. This is not software that you can just click your way through without reading a little of the documentation -- but what would you expect with a powerful tool?

Antwort des Softwareanbieters

von Texifter an 26.4.2019

Dear Shawn,

I like to say those who know it best use it best. As user #4 out of thousands, we can safely pronounce you as "one who knows it best."

Warmest regards,
~Stu

Great tool for analyzing media content

Bewertet am 27.8.2019
Verifizierter Rezensent
Senior Researcher
Forschung, 13-50 Mitarbeiter
Verwendete die Software für: Mehr als 2 Jahre
Quelle des Nutzers 
5/5
Gesamt
4/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: We have been using it for several years in different research projects (politics and media) and even when we performed tasks the tool is not originally designed to perform, DT performed really well (and DT was very supportive!)

Vorteile: Very adaptable to our research aims
Very user-friendly
Coder monitoring/adjudication feature made it possible to coordinate a team of researchers sitting in different countries
Excellent customer support

Nachteile: The visualization of the coding results is a bit dull in terms of design but one can always export results in another programme that creates more impressive visualizations

User-friendly tool w/ excellent customer service

Bewertet am 1.4.2019
Verifizierter Rezensent
Assistant Professor, Mark H. McCormack Department of Sport Management
Hochschulbildung, 201-500 Mitarbeiter
Verwendete die Software für: Mehr als 2 Jahre
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: I began using DiscoverText as a doctoral student in 2013 while conducting research on sport fans' social media usage. Six years later, I still find myself turning to DiscoverText whenever I need to collect social media data. As someone who is not very technology savvy, I find the platform to be quite user-friendly, and the ability to code data right within the platform is extremely beneficial. Beyond the benefits of the tool itself, my interactions with the DiscoverText team are always pleasant and informative. It can be so difficult these days to feel "heard" as a customer, but I don't have to worry about that with DiscoverText. Whenever I have questions or issues, they are quickly answered/remedied by the DiscoverText team.

Vorteile: User-friendly, ability to run multiple feeds, coding capabilities, customer service

Nachteile: I have few things I dislike about DiscoverText. Ability to pull data from Instagram would be great, given consumers' interest in the platform.

Antwort des Softwareanbieters

von Texifter an 22.4.2019

Thanks for the feedback and long term support for our efforts!

Great qualitative analysis tool

Bewertet am 30.8.2019
Alexandra F.
Research Assistant
Forschung, 5.001-10.000 Mitarbeiter
Verwendete die Software für: Mehr als 2 Jahre
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: I have worked on a number of projects using Discovertext, and the experience of coding large qualitative datasets in a relatively short time is a big plus.

Vorteile: The possibility of training the machine into coding massive amounts of data is definitely a plus. Additionally, having multiple human coders train the algorithm allows for interrater reliability and further calibrations.

Nachteile: It is best to take the freedom and fidget with the tool before proceeding and setting up your project, as the documentation is not 100% thorough.

A great Tweet coding software platform for my research

Bewertet am 24.4.2019
Jared W.
Graduate Student
Forschung, 10.001+ Mitarbeiter
Verwendete die Software für: Mehr als 1 Jahr
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
Kundenbetreuung
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: Great tool for analyzing texts from social media, especially Twitter. It makes it especially convenient to code large data sets of Tweets.

Vorteile: As a sociologist, I study online activism and social movements. DiscoverText has been a great way to collect and analyze Tweets related to various protest movements like #MeToo and #BlackLivesMatter.

Nachteile: It took a little time at first to get familiar with the platform, but once I spent some time going through the tutorials I got the hang of it.

Antwort des Softwareanbieters

von Texifter an 26.4.2019

Jared,

Thank-you for your important work on the platform and the nice review.

~Stu

Great for students diving into internet methods!

Bewertet am 1.5.2019
Heather r. W.
Graduate Student
Forschung, Selbstständig
Verwendete die Software für: 6-12 Monate
Quelle des Nutzers 
5/5
Gesamt
4/5
Benutzerfreundlichkeit
4/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Vorteile: I was most interested in the twitter features of DiscoverText when I first set up my account. And I have to say I am thrilled with what the tool can do. When downloaded from the online app, twitter data updates in real time, which is not only in accordance with Twitter ToS, but also gives you the most updated information. The data processing tools are quite amazing if you can figure out how to do it.

Nachteile: There are data restrictions and the export possibilities are limited. So you have to erase old projects to start new ones once you have reached your data capacity.

DiscoverText is a great tool for collecting, sorting, and analyzing data

Bewertet am 25.2.2018
Brittany A.
PhD Student
Verwendete die Software für: Mehr als 1 Jahr
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Vorteile: DiscoverText is a great tool for collecting, sorting, and analyzing data. The platform allows for collection of data from various networks, such as Twitter. I mainly use the platform for coding and machine-classification of tweets. The import feature allows for integration between DiscoverText and other interfaces. For a client project, our data was collected from another toolkit and formatted in an Excel CSV. We were able to import the data into DiscoverText and use the platform to code and machine-classify the tweets. When working with multiple coders, the platform enables you to quickly and efficiently measure inter-coder reliability, which is helpful to determine validity of codes and which categories may need re-classification. I also like the export feature, which allows you to export coding/classification reports. The platform produces different visualizations (e.g. pie charts/graphs) of the coding breakdown, or you can export the entire report into another file (such as a CSV). Overall, I've had a great experience using DiscoverText for both in-class and client research projects. I will continue to use the platform for future research projects, especially the coding and machine-classification functionalities!

Nachteile: When first using the software, it could be a little difficult for a beginning user to identify where all of the features are located and their specific purpose (e.g. exporting reports, buckets, duplicating a dataset). However, the training sessions, video tutorials, and manuals are very insightful and can help immensely with learning of the new features. As with any new platform, it just takes a bit of time to learn all of the features!

Antwort des Softwareanbieters

von Texifter an 7.3.2018

Thanks very much for this detailed review Brittany. As always, if we can do anything to help, drop us a line or schedule a web meeting.

Best,
~Stu

A much better way to scrape data than learning how to code an API

Bewertet am 29.12.2018
Christine A.
Water Treatment Consultant
Umweltdienstleistungen, 1.001-5.000 Mitarbeiter
Verwendete die Software für: Kostenlose Testversion
Quelle des Nutzers 
5/5
Gesamt
4/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: I'm a PhD candidate who straddles the Humanities and Social Sciences, so I use DiscoverText as a research tool.

Vorteile: My review of DiscoverText is a bit limited because I'm really only using it for Twitter. That said, the features are incredible. I know a bit about coding, but the prospect of learning JSON to use Twitter's API was doable but daunting. When I came across DiscoverText I was so pleased to find a way to search, use, and categorize Twitter data that made sense and would save me A LOT of time. I didn't anticipate getting access to so much useful metadata that was easy to navigate and use, so I was pleasantly surprised. The built-in bucket and dataset features are great ways to organize the massive amount of Twitter data that can be collected. The ability to code the data with peers within DiscoverText is also super useful. I really can't exaggerate how many features DiscoverText has that I didn't think I would need but have used to improve the quality of my scholarship.

Nachteile: The software has many features that I didn't find on my own, so the UI could be improved a bit. That said, the one-on-one tutorial that the founder provides helps mitigate this issue. The tutorial videos are helpful too! You'll just have to be prepared to set aside a few hours to really learn the program.

Antwort des Softwareanbieters

von Texifter an 2.1.2019

Dear Christine,

It is really hard to express how inspirational a review like this is. You have really made our day. We are looking at 2019 trying to decide if this is the year to build v2 of a 9 year old interface. Thanks for embracing buckets & datasets; this was a tough sell to some folks over the years, but they are critical to User success.

We are very grateful you took the time to write this generous review. Please write us if we can do anything for you.

Thanks,
~Stu

Unique tool for academic research with a wide range of features

Bewertet am 10.10.2018
Antonia S.
Researcher
Forschung, 13-50 Mitarbeiter
Verwendete die Software für: 6-12 Monate
Quelle des Nutzers 
5/5
Gesamt
4/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: We are an academic institution using Discovertext to study social media use related to disaster preparedness and response. We’ve used the platform to code, filter, classify and analyze historical Twitter data (about 1.5 million tweets), which has opened new opportunities in academic research of social media use. We have used collaborative coding processes and individual coding, the combination of which makes this platform a unique tool for data analysis. We hope it continues to exist and improve as it provides a great service for research like ours.

Vorteile: - The software allows to code and machine-classify thousands of tweets per day through its filtering, search and other advanced features.
- The fact that is cloud-based makes it very convenient to work collaboratively with very large amounts of data from anywhere.
- The metadata and tag cloud features are very useful throughout the whole coding and analysis processes.
Customer support is great and normally very timely.

Nachteile: The software has many extremely useful features, but sometimes it has been hard to keep track of exactly how to use them and where to find them, especially because they are constantly evolving as the developers improve existing features, and add new features and functionalities. It would be helpful to have online User Manual that contains the exact way to use function, what each function does, and how to access them easily.

Antwort des Softwareanbieters

von Texifter an 26.4.2019

Dear Antonia,

It has been a pleasure working with your group and I hope the research continues to bear fruit for you and the team.

We are very grateful for this careful and thoughtful review.

Regards,
~Stu

A perfect tool to explore, collect, search, store, manage, code and classify the Twitter universe.

Bewertet am 3.1.2018
Verifizierter Rezensent
Principal Research Scientist
Forschung, 1.001-5.000 Mitarbeiter
Verwendete die Software für: Mehr als 2 Jahre
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: The ability to work with Twitter data.

Vorteile: As a social scientist, I lack the computational skills to work with Twitter data. In fact, Im not interested in doing data science, I want to do social science. DiscoverText allows me to collect and analyze large batches of Twitter data. Many of my colleagues spend hours having students copy and paste tweets into the Excel. DiscoverText is a breeze.

Nachteile: There are a number of different classification algorithms like linear or logistic regression, decision tree, SVM, and random forest. DiscoverText just uses naive bayes. I wish the software allowed for more different types of these algorithms.

Antwort des Softwareanbieters

von Texifter an 24.1.2018

Thanks for taking the time to write a review. We do have a long term road map that calls for exactly what you are asking for. It is my hope that we can launch a new extension of the platform to host other classifiers. We agree that the inclusion of other approaches would represent an exciting next step in the evolution of the platform. We literally aspire to be the iTunes of machine classifiers ;-)

So, I promise it will happen some day. For now, the uClassify engine that we license is working great on all languages and in all sorts of projects.

~Stu

Honestly,I can say DiscoverText makes analyzing social data not only easier, but also more enjoyable

Bewertet am 1.1.2018
Hossein K.
Research Fellow and Adjunct Professor
Verwendete die Software für: 1-5 Monate
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: It provides me more opportunities for working on my projects. Using it, I have access to many ways for doing research on social media data which have not before.

Vorteile: First, it is so easy to learn and use. Moreover, the DiscoverText founders provided some helpful tutorials and educational videos which are so handy and helpful. This software allows users to makes several datasets of one project. This enables a researcher to work on multi-dimentions of a certain project needless to create different ones. Furthermore, you can create a sample of your data very easily by making a dataset. Its buckets are very interesting also. Additionally, you can make some clouds of data by using cloud explorer feature. Finally, Clustering option is great! it makes working on big data easy and shows the main trends in them quickly.

Nachteile: As I can say, sometimes users may get confused by many links and pages. So, maybe finding what you want becomes difficult and you have to try some ways. Another con, in my point of view, is the obscurity of metadata meanings and algorithms. I cannot understand what some of the means and how they are calculated. Furthermore, I think some of metadata can be presented in some more useful ways. But at all, I should confess the metadata explorer is a great ability!

Antwort des Softwareanbieters

von Texifter an 24.1.2018

Thanks Hossein for an excellent review. We are preparing a new blog post now with a Metadata Dictionary for Gnip Twitter data. We agree that some of the fields are a bit confusing and we hope this new blog post will make the meaning of some of the fields more transparent.

Easy and intuitive research tool, great for qualitative research that involves social media data

Bewertet am 12.6.2018
Verifizierter Rezensent
Lab & Research Spec II
Verwendete die Software für: 1-5 Monate
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: Quick way to collect and analyse data, also very mobile phones and tablets friendly.

Vorteile: Well again, DiscoverText is really intuitive to use, I did read and look at some videos before using it but it wasn't necessary. I have used other qualitative analysis software and although they were a little different, I would say that DiscoverText is the easiest to get familiar with, just set up your themes, categories and start coding. Also something to consider in my opinion is the ease to navigate through the website, not overly complicated, nice blue/gray theme that won't feel heavy after hours spent on the PC.

Nachteile: Only one maybe, if there are a few coders coding at the same time the same project the software can become a little slower.

Antwort des Softwareanbieters

von Texifter an 13.6.2018

Dear Reviewer,

Thanks for this delightful take on the interface. Reading reviews, it is often the case that users underestimate what it might take to overhaul the front end. We would like to, but a bigger company tried in 2013, spent $1M, then gave up, so for now we tinker at the edges to make the experience usable.

I think you are absolutely on target about our goal not to overcomplicate coding (labeling, tagging, or annotation to some). Out first open source tool was devoted to recording observations about text with minimal interaction with a mouse (hence the keystroke coding).

Since then, many layers of functionality have emerged, but at teh core, it is the interface for displaying text/Tweets, the auto-loading of items to be coded, and the project management/measurement features, that are the kernel of our success.

Thanks,
Stu

DiscoverText is unique--it has the best mix of human coding and machine learning I have found.

Bewertet am 6.4.2018
Patricia R.
Prof./Director
Fundraising, 5.001-10.000 Mitarbeiter
Verwendete die Software für: Mehr als 2 Jahre
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: Combines data collection, human coding, machine coding and then easily exports to other software packages for additional analysis. Saves a huge amount of time.

Vorteile: The dashboard allows our lab group to see multiple projects at once and keep track of the data feeds so we know how quickly we are collecting data on particular topics. It also has many useful functions like tracking topics over time, data cleaning support, analyzing social media meta-data and exporting data into other tools like NodeXL.

Nachteile: Most everything is pretty intuitive and support is very fast. My biggest challenge was setting up hierarchical coding schemes, which can be challenging until you create a template that can be reused.

Antwort des Softwareanbieters

von Texifter an 9.4.2018

Dr. Riley,

Thanks for the feedback. We really appreciate it.

~Stu

Useful software, very helpful team

Bewertet am 13.11.2018
Spencer G.
Assistant Professor
Hochschulbildung, 10.001+ Mitarbeiter
Verwendete die Software für: Kostenlose Testversion
Quelle des Nutzers 
4/5
Gesamt
4/5
Benutzerfreundlichkeit
4/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
Unwahrscheinlich Äußerst wahrscheinlich

Kommentare: I used DiscoverText after hearing about them on the Association of Internet Researchers mailing list. Stu and his team helped me put together a Twitter dataset that I'd been trying to put together through other methods—never without any success. This is a huge step forward for some of the research that I'm trying to do; I'm already getting some interest in the data and my analysis of it, and I couldn't have done it without DiscoverText!

Vorteile: DiscoverText worked exactly as hoped, but the most impressive thing is how helpful and personal the DiscoverText team was with helping me with the particular request that I had.

Nachteile: Figuring out how to download the raw data took a little bit of time. I can't blame DiscoverText for wanting me to stick with their interface and their tools, but it was still a little annoying that it took a while to get to what I needed.

Antwort des Softwareanbieters

von Texifter an 14.11.2018

Professor Greenhalgh,

Thank-you for taking the time to write a detailed review. It really helps us out.

I feel it is important to clarify that the frustration you express is with a policy set by Twitter that we built into DiscoverText to stay compliant with the Twitter Terms of Service. You are not alone wanting more direct access to raw data, but the issue was and remains that Twitter does not allow us to provide that direct raw data download access without:

a) some transformation of the data, and
b) a daily export limit of 50,000 items.

We did not make the rule; we simply obeyed it.

For the record, our platform's live connection to the Twitter display, and our ability to suppress deleted Tweets, are two of the many reasons why you are better off keeping data in DiscoverText. For inter-operability with Gephi or NodeXL, we still have the graphml export option.

At the very least, using our tools to create clean, legal, focused, exports is an option.

~Stu

Much easier to code textual datasets than using spreadsheets

Bewertet am 12.12.2017
John P.
Consultant
Informationsdienst, Selbstständig
Verwendete die Software für: Mehr als 1 Jahr
Quelle des Nutzers 
4/5
Gesamt
4/5
Benutzerfreundlichkeit
4/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
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Kommentare: Can remove duplicate to reduce the time it takes to code a dataset.
Great for: employee satisfaction surveys, customer satisfaction surveys, marketing surveys
Can supply your own data, such as from a survey, in various formats including text and Excel spreadsheet.
Can acquire data from social media including Facebook, Twitter, and others.

Vorteile: Working as an independent consultant, I have had opportunities to help some clients analyze textual data through coding exercises. The first exercise was to examine customer feedback that had been collected by a weel-known hotel/travel review site. The customer's feedback data was tallied and processed with spreadseets, which was very cumbersome because quite a bit of horizontal scrolling across the spreadsheet's columns was required to enter customer's sentiments about the hotel. After becoming familiar with DiscoverText, I estimated that the same exercise could probably have been accomplished in half the time. Coding can be designed so that the coders simply have to select a number (e.g., 1 through 5) or from a list of predefined sentiments (e.g., staff was friendly, the hotel was clean, elevator did not work, etc.). More recently I have used DiscoverText on several projects, including attendee's comments about a local music festival, an employee satisfaction survey, and tweets about a clothing and accessories brand.

Nachteile: The interface takes a little getting used to. I suggest you practice with a small sample dataset before launching into a huge research project.

Discover Text for academic study

Bewertet am 30.1.2019
Morgan D.
Graduate Research Fellow
Forschung, 1.001-5.000 Mitarbeiter
Verwendete die Software für: Kostenlose Testversion
Quelle des Nutzers 
5/5
Gesamt
4/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
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Kommentare: Discover text has been an incredible resource to explore crisis communication. The founder is particularly dedicated to his product and has held numerous one on one tutorial sessions for me.

Vorteile: The advanced filtration tool allows you to sort of metadata tags like the geolocation of a tweet, which is extremely useful for academic work. This software is a great platform for an engineering academic like me to ease into the fields of text analytics and sentiment analysis.

Nachteile: Like any software there is a learning curve for Discover text. Rely on the vast tutorial library to get through tasks., and sometimes the distinctions between data levels (buckets vs datasets) can be confusing.

Antwort des Softwareanbieters

von Texifter an 1.2.2019

Morgan,

That is a very generous review. You are right that as a founder, the software acquires the status of a family member; almost a beloved child.

There was a time "buckets" were on the chopping block (not my idea) and I fought it. Buckets are critical parts of projects. Here is how I explain it to people now:

ARCHIVES: Raw text and metadata (static or live feeds updating) that can be manipulated without changing the raw data archive.

BUCKETS: Sub-sets of raw data (search, filter, code, cluster, classify and then mix and match techniques to make buckets).

DATASETS: Samples for human coding and machine learning.

One advantage to this structure is continual LOW-RISK experimentation. Try one pathway, if it works, keep going, if not, try an alternate route informed by previous failures.

People often ask: what comes first? Once the data is loaded, that is up to you. There is no A,B, C path the same for all. The platform supports qual, quant, and mixed methods.

Great Collaborative Text Analytics System

Bewertet am 29.7.2018
Verifizierter Rezensent
Data Analyst
Staatsverwaltung
Verwendete die Software für: 6-12 Monate
Quelle des Nutzers 
5/5
Gesamt
4/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis

Vorteile: DiscoverTest (DT) is great at what it was intended to be used for. DT makes it easy to schedule fetches from leading social media and information websites, and allows the user to specifically get the data they are looking for. We have used DT for 2 different projects so far and it seems to work great for our team of analysts.

Nachteile: DiscoverTest has a relatively steep learning curve, and therefore can be intimidating to new users. It is well worth your time though, as the features far outweigh the learning curve.

Antwort des Softwareanbieters

von Texifter an 10.8.2018

DiscoverTest has a relatively steep learning curve, and therefore can be intimidating to new users. It is well worth your time though, as the features far outweigh the learning curve.

Thank you for your review. DiscoverText is indeed a powerful tool, and therefore does take some time to learn all of its features. We try to make this easier with our training resources.

We offer web demo meetings, video tutorials, and a knowledge base full of documentation that we hope you find insightful and helpful when learning the features of DiscoverText and Sifter.

Stu Shulman, the founder of Texifter, conducts webinars all the time to train people on the features best suited for research. You can schedule a webinar at:
https://calendly.com/discovertext

Video tutorials:
https://discovertext.com/tag/video/

Support Documentation & Knowledge Base:
https://texifter.zendesk.com/hc/en-us

Best regards,
Stu

I've been using it for several years for analyzing customer data and Twitter data.

Bewertet am 14.12.2017
Gabriela Z.
Independent Researcher
Computer-Software
Verwendete die Software für: Mehr als 2 Jahre
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
4/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
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Kommentare: It's easy to create and code a dataset, and it is a particularly useful software to work with a team of coders in the same dataset.

Vorteile: My favorite feature about this software is the fact that it allows multiple coders to easily work on a coding project. So if you have a lot of data, you can load the data on DiscoverText, set up some codes, and have several people work at the same time with coding. It will provide you with a report of what each coder did for how long etc, and also will allow you to export the results.
You can also import data directly from Twitter using the search API. Coders can see the actual tweet when coding, which helps speed up the coding process. You can also export the data to NodeXL in order to generate social graph and calculate social network analysis metrics.
For a fee, it is also possible to get access to GNIP and the entire historical archive of tweets.
DiscoverText is not limited to Twitter, you can import data from other sources (including SurveyMonkey). As a researcher working with Twitter, for me the most valuable tool is the ability to easily create and code a Twitter dataset.

Nachteile: Sometimes it will let two coders work on the same item if they access the item at the same time. Not allowing this could speed up the process.

Our goal was to get a historical tweets and do an linguistic analysis.

Bewertet am 12.3.2018
Egor S.
Research Assistant
Verwendete die Software für: 1-5 Monate
Quelle des Nutzers 
4/5
Gesamt
2/5
Benutzerfreundlichkeit
4/5
Eigenschaften & Funktionalitäten
4/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis

Vorteile: - teamwork friendly
- support different types of file extraction
- directly support of Gnip Feed Management
- parallel possibility to work on different project
- support of: Facebooks, LinkedLn

Nachteile: - just 15 exports could be saved parallel in the system at any given time (so sometimes you need more files to extract parallel)
- exports have just 1 week time of expiration (it is tooooo small)
- don't have command line API

Antwort des Softwareanbieters

von Texifter an 15.3.2018

Egor,

Thanks for taking the time to write a review. It contains some good ideas, some of which we might be able to act on, but others are beyond our control.

The regulation of Twitter exports, for example, is set by the Terms of Service of Twitter. We are specifically barred, as are all vendors, from setting up a command line API to facilitate the process. The save as CSV is a very strict guideline and engineering what you want would result in Texifter losing access to Twitter data. So, it is a "con" of working with Twitter data, not DiscoverText.

I'd like to hear more about why you need to store links to more than 15 exports simultaneously. Since you can only create 1/day of 50,000 Tweets, and the purpose is to export it, not store the CSV link in a list inside DiscoverText, why would you need a list of more than 15 links to files? Presumably you have already exported. I have the same question with the duration. Once the data is downloaded, why must the link endure?

~Stu

It's a great tool to code big or even vast amounts of data in an efficient way. It work very well!

Bewertet am 8.6.2018
Max S.
Staff Position
Verwendete die Software für: Mehr als 1 Jahr
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
4/5
Kundenbetreuung
4/5
Preis-Leistungs-Verhältnis
Wahrscheinlichkeit der Weiterempfehlung:
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Vorteile: It is easy to use, very intuitive, it gives you the basic options and functions in a clear design. Through the annotation tool, it is easy to amend the existing coding scheme and hint to anything problematic. This way you can also easily communicate with other users who you work on a project with. I really like the elegance of the program! It works very well for both rather simple (even binary) and truly elaborate and detailed coding schemes.

Nachteile: the only real problem I encountered was that it can be annoying to jump back to an already coded item (for instance if you realized you made a mistake or want to add an annotation): if you use the "back" function it brings you to the previous numerical item which might not be the one you coded but one someone else is coding at the same time. Then you have to keep clicking "back" until your item reappears. This should be fixed. It is, however, a rare issue.

Antwort des Softwareanbieters

von Texifter an 11.6.2018

Max,

Thanks for this idea and the generous review. It makes perfect sense and we will engineer a solution for that immediately.

Stu

Excellent software and after sales support

Bewertet am 23.1.2018
Joseph D.
Postdoctoral Fellow
Forschung
Verwendete die Software für: Mehr als 1 Jahr
Quelle des Nutzers 
5/5
Gesamt
5/5
Benutzerfreundlichkeit
5/5
Eigenschaften & Funktionalitäten
5/5
Kundenbetreuung
5/5
Preis-Leistungs-Verhältnis
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Kommentare: Made my research possible, cant overstate how important it has been for me!

Vorteile: Discovertext has enabled me, a non-IT specialist, to create, sort and purchase large scale twitter data sets for qualitative academic research. As a platform it is extremely user friendly and intuitive and took very little time for me to become comfortable with. It is also always accessible, I have logged in all over the world and have never had any problems with the platform. However, like all software platforms, the platform is only as good as the after sales support. Thankfully, Discovertext has the best post-sales service of any company I have worked with, they are always accessible and you always get a real human at the end of the phone who knows the software inside and out where else do you regularly get to speak to the founder of the software and the CEO of the company on a regular basis for after sales help. Thus, to me, you can't go wrong with discovertext and I have no complaints.