This document discusses research on customer communication about Toyota vehicle recalls on Twitter. The researchers analyzed over 37,000 tweets mentioning "Toyota" and "recall" to study how the crisis was discussed online. Key findings include that discussion topics peaked at certain times and sentiment became more polarized during peaks. While participation increased overall, individual contributions remained uniform. Differences were found between sentiments of highly active users versus all participants. The researchers propose further analysis of topic dynamics, comparative case studies, and content and network analysis of tweets.
Words are part of almost every marketplace interaction. Online reviews, customer service calls, press releases, marketing communications, and other interactions create a wealth of textual data. But how can marketers best use such data?
Brand Management; Customer Reviews; Digital Marketing – Customer; Marketing Analytics; Marketing Communications; Marketing Metrics; Social Media
There is a gap between data and analytics growth and firm growth – Investing in data and analytics through the lens of the customer equity framework can help close that gap.
Reimer hanusch tandoc_2018_influence of algorithmic vs qualitative feedbackJulius Reimer
„The Influence of Algorithmic vs Qualitative Audience Feedback on Journalists’ Work“, presentation at the 68th annual conference of the International Communication Association (ICA) in Prague, 28 May 2018 (together with Folker Hanusch and Edson Tandoc, Jr.).
Words are part of almost every marketplace interaction. Online reviews, customer service calls, press releases, marketing communications, and other interactions create a wealth of textual data. But how can marketers best use such data?
Brand Management; Customer Reviews; Digital Marketing – Customer; Marketing Analytics; Marketing Communications; Marketing Metrics; Social Media
There is a gap between data and analytics growth and firm growth – Investing in data and analytics through the lens of the customer equity framework can help close that gap.
Reimer hanusch tandoc_2018_influence of algorithmic vs qualitative feedbackJulius Reimer
„The Influence of Algorithmic vs Qualitative Audience Feedback on Journalists’ Work“, presentation at the 68th annual conference of the International Communication Association (ICA) in Prague, 28 May 2018 (together with Folker Hanusch and Edson Tandoc, Jr.).
Need Response 1The subcomponent of crowdsourcing ICT platform.docxvannagoforth
Need Response 1:
The subcomponent of crowdsourcing ICT platform technological architecture I would like to discuss is that gives additionally created an examination concerning public text information (for instance blog postings, comments, appraisals, etc.) and setting up this information sources using sentiment mining tools. The Web has changed the way wherein people express their emotions, offering them the capacity to post comments and reviews on business things and express their points of view on a a huge amount of issues in parties, talk get-togethers, visit rooms, long-broaden agreeable correspondence get-togethers and web diaries. This customer passed on the substance has been seen as a tremendous wellspring of business and political information. Notwithstanding, the tremendous the degree of this information and its normal language structure makes it difficult to remove the consistent areas, for instance, the general inclination/assessment (for instance positive, negative or sensible) on the particular subject (for instance a thing/affiliation or another methodology proposition) and the specific issues raised about it by the customers/visitors of these objectives. It is hidden motivation has been to enable firms to research online overviews and comments entered by customers of their things in various review districts, web diaries, social affairs, etc., in order to arrive at general judgments as for whether customers adored the thing or not (supposition assessment), and moreover continuously express finishes concerning features (traits) of the thing that has been commented on insistently or conflictingly (features extraction and examination).
This subcomponent performs three tasks, firstly it classifies the opinion text, a document which includes various declarations like a dialogue or a blog spot conveying a positive, negative or unprejudiced end. This is suggested as the record level evaluation examination. Secondly further focusing on sentence-level which deals with the gathering of a sentence as objective or passionate, it organizes each sentence in such a structure, that atmosphere it is a unique or targets (demonstrating whether it can express the inclination or not). For each sentence that is a conceptual (infers conveying an inclination) further, the portrayal is done as imparting an appositive, negative or unprejudiced supposition. Lastly extracting the most commented features of the commented articles, and for each commented feature further classification of relevant opinion is executed as positive, negative or unprejudiced.
References
Janssen, M., Wimmer, M. A., & Deljoo, A. (Eds.). (2015). Policy practice and digital science: Integrating complex systems, social simulation and public administration in policy research (Vol. 10). Springer
Need response 2:
nformation and communication technology platform has an important role to play in active crowdsourcing. A policy maker of a government agency initiates ...
Tweetfix is a visualization platform, developed for the Fix the Fixing european project, where users can explore the results of crowdsourced data analytics from Social Media on well-known Match Fixing cases.
The Effect of Bad News and CEO Apology of Corporate on User Responses in Soci...THE LAB h
by Hoh Kim, Jaram Park, Meeyoung Cha, Jaeseung Jeong
Graduate School of Culture Technology, Korea Advanced Institute of Science and Technology (KAIST), 305–701, Daejeon, Republic of Korea
Published in 2015 @ PLoS ONE 10(5): e0126358. doi:10.1371/journal.pone.0126358
IEEE PROJECTS 2016 - 2017
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Project Domain list 2016
1. IEEE based on datamining and knowledge engineering,
2. IEEE based on mobile computing,
3. IEEE based on networking,
4. IEEE based on Image processing,
5. IEEE based on Multimedia,
6. IEEE based on Network security,
7. IEEE based on parallel and distributed systems
Project Domain list 2016
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2016
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
5. IOT Projects
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US:-
1 CRORE PROJECTS
Door No: 66 ,Ground Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 7708150152
How could a product or service is reasonably evaluated by anyone in the shortest time? A million dollar
question but it is having a simple answer: Sentiment analysis. Sentiment analysis is consumers review on
products and services which helps both the producers and consumers (stakeholders) to take effective and
efficient decision within a shortest period of time. Producers can have better knowledge of their products
and services through the sentiment analysis (ex. positive and negative comments or consumers likes and
dislikes) which will help them to know their products status (ex. product limitations or market status).
Consumers can have better knowledge of their interested products and services through the sentiment
analysis (ex. positive and negative comments or consumers likes and dislikes) which will help them to know
their deserving products status (ex. product limitations or market status). For more specification of the
sentiment values, fuzzy logic could be introduced. Therefore, sentiment analysis with the help of fuzzy logic
(deals with reasoning and gives closer views to the exact sentiment values) will help the producers or
consumers or any interested person for taking the effective decision according to their product or service
interest.
International Journal of Computer Science, Engineering and Information Techno...ijcseit
How could a product or service is reasonably evaluated by anyone in the shortest time? A million dollar
question but it is having a simple answer: Sentiment analysis. Sentiment analysis is consumers review on
products and services which helps both the producers and consumers (stakeholders) to take effective and
efficient decision within a shortest period of time. Producers can have better knowledge of their products
and services through the sentiment analysis (ex. positive and negative comments or consumers likes and
dislikes) which will help them to know their products status (ex. product limitations or market status).
Consumers can have better knowledge of their interested products and services through the sentiment
analysis (ex. positive and negative comments or consumers likes and dislikes) which will help them to know
their deserving products status (ex. product limitations or market status). For more specification of the
sentiment values, fuzzy logic could be introduced. Therefore, sentiment analysis with the help of fuzzy logic
(deals with reasoning and gives closer views to the exact sentiment values) will help the producers or
consumers or any interested person for taking the effective decision according to their product or service
interest.
How could a product or service is reasonably evaluated by anyone in the shortest time? A million dollar
question but it is having a simple answer: Sentiment analysis. Sentiment analysis is consumers review on
products and services which helps both the producers and consumers (stakeholders) to take effective and
efficient decision within a shortest period of time. Producers can have better knowledge of their products
and services through the sentiment analysis (ex. positive and negative comments or consumers likes and
dislikes) which will help them to know their products status (ex. product limitations or market status).
Consumers can have better knowledge of their interested products and services through the sentiment
analysis (ex. positive and negative comments or consumers likes and dislikes) which will help them to know
their deserving products status (ex. product limitations or market status). For more specification of the
sentiment values, fuzzy logic could be introduced. Therefore, sentiment analysis with the help of fuzzy logic
(deals with reasoning and gives closer views to the exact sentiment values) will help the producers or
consumers or any interested person for taking the effective decision according to their product or service
interest.
Current Research Questions in Word of Mouth CommunicationAlexander Rossmann
Word of mouth (WOM) communication, long recognized as a highly influential source of information, has taken on new importance with the proliferation of online WOM. The rise of online forums and communities has dramatically increased the scope of word of mouth marketing, allowing consumers greater access to information from subject matter experts and other key influentials who impact new purchases. Online WOM data have been widely used in the literature to examine topics such as the impact of WOM recommendations and reviews, brand community involvement, and product adoption. For all the valuable contributions made by WOM research, a lot of important questions still remain unexplored. One is delineating the preconditions for user engagement in WOM communication; another is exploring the role of WOM content and WOM context on the efficacy of WOM in general. And there is final area where research is needed, focusing on organizational capabilities firms need in order to foster the impact of WOM communication on purchasing behavior.
Brands image across the internet including social mediaSotrender
Over the years, we've developed and delivered dozens of reports for our clients, partners, and the media. From smaller, cyclical anlayses to big audits or year-end reports - we love to be challenged and squeeze out everything we can from our data. We constantly look for ways to improve our alogithms and educate the market about what data can tell them and how they can use it in every day work or in planning their strategy.
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOK dannyijwest
The 21st century has been characterized by an increased attention to social networks. Nowadays, going 24
hours without getting in touch with them in some way has become difficult. Facebook and Twitter, these
social platforms are now part of everyday life. Thus, these social networks have become important sources
to be aware of frequently discussed topics or public opinions on a current issue. A lot of people write
messages about current events, give their opinion on any topic and discuss social issues more and more.
Need Response 1The subcomponent of crowdsourcing ICT platform.docxvannagoforth
Need Response 1:
The subcomponent of crowdsourcing ICT platform technological architecture I would like to discuss is that gives additionally created an examination concerning public text information (for instance blog postings, comments, appraisals, etc.) and setting up this information sources using sentiment mining tools. The Web has changed the way wherein people express their emotions, offering them the capacity to post comments and reviews on business things and express their points of view on a a huge amount of issues in parties, talk get-togethers, visit rooms, long-broaden agreeable correspondence get-togethers and web diaries. This customer passed on the substance has been seen as a tremendous wellspring of business and political information. Notwithstanding, the tremendous the degree of this information and its normal language structure makes it difficult to remove the consistent areas, for instance, the general inclination/assessment (for instance positive, negative or sensible) on the particular subject (for instance a thing/affiliation or another methodology proposition) and the specific issues raised about it by the customers/visitors of these objectives. It is hidden motivation has been to enable firms to research online overviews and comments entered by customers of their things in various review districts, web diaries, social affairs, etc., in order to arrive at general judgments as for whether customers adored the thing or not (supposition assessment), and moreover continuously express finishes concerning features (traits) of the thing that has been commented on insistently or conflictingly (features extraction and examination).
This subcomponent performs three tasks, firstly it classifies the opinion text, a document which includes various declarations like a dialogue or a blog spot conveying a positive, negative or unprejudiced end. This is suggested as the record level evaluation examination. Secondly further focusing on sentence-level which deals with the gathering of a sentence as objective or passionate, it organizes each sentence in such a structure, that atmosphere it is a unique or targets (demonstrating whether it can express the inclination or not). For each sentence that is a conceptual (infers conveying an inclination) further, the portrayal is done as imparting an appositive, negative or unprejudiced supposition. Lastly extracting the most commented features of the commented articles, and for each commented feature further classification of relevant opinion is executed as positive, negative or unprejudiced.
References
Janssen, M., Wimmer, M. A., & Deljoo, A. (Eds.). (2015). Policy practice and digital science: Integrating complex systems, social simulation and public administration in policy research (Vol. 10). Springer
Need response 2:
nformation and communication technology platform has an important role to play in active crowdsourcing. A policy maker of a government agency initiates ...
Tweetfix is a visualization platform, developed for the Fix the Fixing european project, where users can explore the results of crowdsourced data analytics from Social Media on well-known Match Fixing cases.
The Effect of Bad News and CEO Apology of Corporate on User Responses in Soci...THE LAB h
by Hoh Kim, Jaram Park, Meeyoung Cha, Jaeseung Jeong
Graduate School of Culture Technology, Korea Advanced Institute of Science and Technology (KAIST), 305–701, Daejeon, Republic of Korea
Published in 2015 @ PLoS ONE 10(5): e0126358. doi:10.1371/journal.pone.0126358
IEEE PROJECTS 2016 - 2017
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Project Domain list 2016
1. IEEE based on datamining and knowledge engineering,
2. IEEE based on mobile computing,
3. IEEE based on networking,
4. IEEE based on Image processing,
5. IEEE based on Multimedia,
6. IEEE based on Network security,
7. IEEE based on parallel and distributed systems
Project Domain list 2016
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2016
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
5. IOT Projects
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US:-
1 CRORE PROJECTS
Door No: 66 ,Ground Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 7708150152
How could a product or service is reasonably evaluated by anyone in the shortest time? A million dollar
question but it is having a simple answer: Sentiment analysis. Sentiment analysis is consumers review on
products and services which helps both the producers and consumers (stakeholders) to take effective and
efficient decision within a shortest period of time. Producers can have better knowledge of their products
and services through the sentiment analysis (ex. positive and negative comments or consumers likes and
dislikes) which will help them to know their products status (ex. product limitations or market status).
Consumers can have better knowledge of their interested products and services through the sentiment
analysis (ex. positive and negative comments or consumers likes and dislikes) which will help them to know
their deserving products status (ex. product limitations or market status). For more specification of the
sentiment values, fuzzy logic could be introduced. Therefore, sentiment analysis with the help of fuzzy logic
(deals with reasoning and gives closer views to the exact sentiment values) will help the producers or
consumers or any interested person for taking the effective decision according to their product or service
interest.
International Journal of Computer Science, Engineering and Information Techno...ijcseit
How could a product or service is reasonably evaluated by anyone in the shortest time? A million dollar
question but it is having a simple answer: Sentiment analysis. Sentiment analysis is consumers review on
products and services which helps both the producers and consumers (stakeholders) to take effective and
efficient decision within a shortest period of time. Producers can have better knowledge of their products
and services through the sentiment analysis (ex. positive and negative comments or consumers likes and
dislikes) which will help them to know their products status (ex. product limitations or market status).
Consumers can have better knowledge of their interested products and services through the sentiment
analysis (ex. positive and negative comments or consumers likes and dislikes) which will help them to know
their deserving products status (ex. product limitations or market status). For more specification of the
sentiment values, fuzzy logic could be introduced. Therefore, sentiment analysis with the help of fuzzy logic
(deals with reasoning and gives closer views to the exact sentiment values) will help the producers or
consumers or any interested person for taking the effective decision according to their product or service
interest.
How could a product or service is reasonably evaluated by anyone in the shortest time? A million dollar
question but it is having a simple answer: Sentiment analysis. Sentiment analysis is consumers review on
products and services which helps both the producers and consumers (stakeholders) to take effective and
efficient decision within a shortest period of time. Producers can have better knowledge of their products
and services through the sentiment analysis (ex. positive and negative comments or consumers likes and
dislikes) which will help them to know their products status (ex. product limitations or market status).
Consumers can have better knowledge of their interested products and services through the sentiment
analysis (ex. positive and negative comments or consumers likes and dislikes) which will help them to know
their deserving products status (ex. product limitations or market status). For more specification of the
sentiment values, fuzzy logic could be introduced. Therefore, sentiment analysis with the help of fuzzy logic
(deals with reasoning and gives closer views to the exact sentiment values) will help the producers or
consumers or any interested person for taking the effective decision according to their product or service
interest.
Current Research Questions in Word of Mouth CommunicationAlexander Rossmann
Word of mouth (WOM) communication, long recognized as a highly influential source of information, has taken on new importance with the proliferation of online WOM. The rise of online forums and communities has dramatically increased the scope of word of mouth marketing, allowing consumers greater access to information from subject matter experts and other key influentials who impact new purchases. Online WOM data have been widely used in the literature to examine topics such as the impact of WOM recommendations and reviews, brand community involvement, and product adoption. For all the valuable contributions made by WOM research, a lot of important questions still remain unexplored. One is delineating the preconditions for user engagement in WOM communication; another is exploring the role of WOM content and WOM context on the efficacy of WOM in general. And there is final area where research is needed, focusing on organizational capabilities firms need in order to foster the impact of WOM communication on purchasing behavior.
Brands image across the internet including social mediaSotrender
Over the years, we've developed and delivered dozens of reports for our clients, partners, and the media. From smaller, cyclical anlayses to big audits or year-end reports - we love to be challenged and squeeze out everything we can from our data. We constantly look for ways to improve our alogithms and educate the market about what data can tell them and how they can use it in every day work or in planning their strategy.
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOK dannyijwest
The 21st century has been characterized by an increased attention to social networks. Nowadays, going 24
hours without getting in touch with them in some way has become difficult. Facebook and Twitter, these
social platforms are now part of everyday life. Thus, these social networks have become important sources
to be aware of frequently discussed topics or public opinions on a current issue. A lot of people write
messages about current events, give their opinion on any topic and discuss social issues more and more.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
5. What’s the difference? Opinion leaders are hard to identify Much more data and richer information Possibility to track data automatically and analyze them (digital information, ...) very fast (e.g. direct feedback on campaigns) Everybody has a voice – risks and chances for companies Long tail – opinion gathering Choice of words – no strict rules like in press releases, different styles because of different platforms 3 Customer Communication in Twitter
6. Research Questions Goals: getting a deeper understanding about the dynamics of the structures of communication, the participation of the stakeholder and their sentiments in the communication. Are crisis-related issues in twitter discussed (like in the classic media) and are these discussions characterized by peaks and buzzing-stages? Do involved user post higher frequented in peaks than in buzzing stages? Are the postings in the peaks filled with more sentiment-words than in the buzzing stages? Is there a difference between sentiments in Tweets created by power-tweeters (PT) only and the sentiments in Tweets created by all participants of the sample? 4 Customer Communication in Twitter
7. Agenda Motivation and Background Related Work Research Design Summary Research Approach for the further study 5 Customer Communication in Twitter
8. Sentiment in Twitter Messages Sentiment Analysis Sentiment analysis of Tweets: Events in the social, political, cultural and economic sphere do have a significant, immediate and highly specific effect on the various dimensions of public mood (Bollen et al., 2009). Link measures of public opinion derived from polls to sentiment measured from Twitter messages: Sentiment word frequencies in contemporaneous Twitter messages do correlate with several public opinion time series such as surveys on consumer confidence and political opinion over the 2008 to 2009 period (O’Connor et al., 2010). Study of political tweets around the 2009 German federal election: Tweet sentiment (e.g., positive and negative emotions associated with a politician) corresponds closely to voters’ political preferences(Tumasjanet al., 2010). 6 Customer Communication in Twitter
9. Agenda Motivation and Background Related Work Research Design Summary Research Approach for the further study 7 Customer Communication in Twitter
10. Proceeding Objects ofstudy: the Top10 players in theautomotiveindustry Identification of appropriate keywords using classic print media: Identification of keywords by scanning the New York Times over a periode of two weeks, analyzing these articles which are related to one of the carmakers. Structural analysis of the course topics: Observation, analysis and documentation of public communication inTwitter using the keywords found with the help of a software prototype Cleaningupthedata 8 Customer Communication in Twitter
11. Case selection Identificationof an issue The large-scalecarrecall due to a technical fault in the gas pedals and thebreaks Usingthekeyword-combination „recall/-s“, „Toyota“ Implementation ofthe Issue Scanning fortheperiode 13-31 calendarweek: 732.003 Tweets: „Toyota“ 37.232 Tweets: „recall“ und „Toyota“ 9 Customer Communication in Twitter
14. Sentiment Analysis Classifyingthepolarityof a giventextatthedocument, sentence, orfeature/aspectlevel Linguisticdimensions Positive emotions (positive feelings, optimism) Negative emotions (anger, anxiety, sadness) Example: Creatingsentimentprofileforcompanies, partiesoraffiliatedindividuals (e.g., in the form of positive/negative-emotion scales) 12 Customer Communication in Twitter
15. Findings 13 Customer Communication in Twitter Uniform percentage of sentiment words in the discussion A clear tendency of a stronger polarization in peaks
16. 14 Customer Communication in Twitter Findings Isthere a differencebetweensentiments in Tweets createdby power-tweeters (PT) only and thesentiments in Tweets createdby all participantsofthesample?
17. Agenda Motivation and Background Research Approaches Related Work Summary Research Approach for the further study 15 Customer Communication in Twitter
18. Summary Organization-relatedissuesarediscussed in Twitter Usingtheissuescanningkeywordscanidentifytopicsfortrackingdynamics In crisis situations, more individuals participate in the discussion (the contribution per user does not rise) In peak periods, there are clear trends in the discussion to positive or negative sentiments Measures may differ in different types of discussion 16 Customer Communication in Twitter
19. Agenda Motivation and Background Related Work Research Design Summary Research Approaches for the further study 17 Customer Communication in Twitter