Theory top 5 presentation
•Download as PPT, PDF•
0 likes•564 views
Uncertainty reduction theory proposes that when strangers meet for the first time, they will try to reduce uncertainty about each other through interactive conversation, asking third parties about the other person, or passive observation. The theory explains that people use interactive, active, and passive methods of uncertainty reduction in everyday situations like meeting a professor, at a bar, or online dating.
Report
Share
Report
Share
Recommended
Uncertainty Reduction
What happens when people meet and have little information about each other? How do they go about coming to know each other?
Comm201 Uncertainty Reduction Theory- Petrucci
Uncertainty Reduction Theory (URT) was developed in 1975 by Charles Berger and Richard Calabrese to explain how people communicate at the beginning of interactions in order to reduce uncertainty. URT posits that when strangers meet, they immediately seek ways to predict each other's behaviors and reduce uncertainty. While URT focuses on reducing uncertainty in initial interactions, Michael Sunnafrank's Predicted Outcome Value Theory argues that people are more motivated by potential rewards than uncertainty reduction. URT also identifies three strategies for reducing uncertainty: passive observation, active information-seeking from third parties, and direct interactive communication through interrogation or self-disclosure.
Uncertainty Reduction Theory
The Uncertainty Reduction Theory posits that people seek to reduce uncertainty through communication in initial interactions in order to increase predictability. There are three main motivations for reducing uncertainty: anticipation of future interaction, incentive value of the interaction, and explaining deviant behavior. The theory outlines seven axioms about how uncertainty is reduced through verbal communication, nonverbal expressions, information seeking behaviors, self-disclosure, reciprocity, perceived similarities, and shared social networks. People also engage in plan-based message production to subtly influence others' behaviors according to their own goals.
Uncertainty Reduction Theory- Katie Corbin & Haley Sudduth- COMM 301
1) Uncertainty Reduction Theory, proposed by Charles Berger, focuses on how human communication is used to gain knowledge and reduce uncertainty in initial interactions and relationships.
2) The theory proposes that people are motivated to reduce uncertainty through communication behaviors like self-disclosure, information seeking, and developing similarities.
3) Berger developed axioms and theorems about how specific communication behaviors relate to uncertainty and influence relationship development over time. However, some aspects of the theory have been criticized or expanded on.
Uncertainty Reduction Theory G2 COMM2378
The document summarizes Uncertainty Reduction Theory, which proposes that people communicate to reduce uncertainty and discomfort when meeting strangers. It describes the theory's key aspects: (1) it identifies three strategies people use to reduce uncertainty - observing, asking others, direct communication; (2) it outlines three phases of relationships as uncertainty decreases over time; (3) it lists eight axioms about how communication and factors like intimacy, liking, and similarity impact uncertainty; (4) it discusses how theorems are derived from the axioms to make predictions. The document also notes some strengths and weaknesses of the theory and provides an example case study comparing how Koreans and Americans initially communicate to reduce uncertainty.
Uncertainty reduction theory
This document summarizes Charles Berger's Uncertainty Reduction Theory. The theory proposes that there are two types of uncertainty - behavioral and cognitive - and that people seek to reduce uncertainty about others through verbal and nonverbal communication, information seeking, self-disclosure, and focusing on similarities. It also discusses methods for coping with uncertainty, including passive, active, interactive, and hedging strategies. Finally, it briefly introduces William Gudykunst's Anxiety/Uncertainty Management Theory about how higher anxiety can lead to misunderstandings without mindful communication, especially between strangers.
Uncertainty Reduction Theory
Charles Berger's uncertainty reduction theory posits that new relationships involve uncertainty and communication aims to reduce this uncertainty. There are different types of uncertainty including behavioral and cognitive uncertainty. Berger outlines eight axioms that can be paired to produce 28 theorems about how communication reduces uncertainty. Some strategies for reducing uncertainty include seeking information from the other person directly or indirectly, choosing an appropriate level of plan complexity, and amending plans over time based on new information. However, some critiques argue that not all the axioms and theorems are valid and that uncertainty reduction may not be the sole driver of early communication between people.
Uncertainty reduction
Uncertainty reduction theory (URT) proposes that people are motivated to reduce uncertainty in interactions with others. The theory outlines seven factors that influence interpersonal exchanges, including verbal/nonverbal communication and information seeking. Higher uncertainty creates distance while nonverbal cues can help reduce it. URT describes ways people passively, actively, and interactively seek information about others to predict their behavior and feelings of uncertainty.
Recommended
Uncertainty Reduction
What happens when people meet and have little information about each other? How do they go about coming to know each other?
Comm201 Uncertainty Reduction Theory- Petrucci
Uncertainty Reduction Theory (URT) was developed in 1975 by Charles Berger and Richard Calabrese to explain how people communicate at the beginning of interactions in order to reduce uncertainty. URT posits that when strangers meet, they immediately seek ways to predict each other's behaviors and reduce uncertainty. While URT focuses on reducing uncertainty in initial interactions, Michael Sunnafrank's Predicted Outcome Value Theory argues that people are more motivated by potential rewards than uncertainty reduction. URT also identifies three strategies for reducing uncertainty: passive observation, active information-seeking from third parties, and direct interactive communication through interrogation or self-disclosure.
Uncertainty Reduction Theory
The Uncertainty Reduction Theory posits that people seek to reduce uncertainty through communication in initial interactions in order to increase predictability. There are three main motivations for reducing uncertainty: anticipation of future interaction, incentive value of the interaction, and explaining deviant behavior. The theory outlines seven axioms about how uncertainty is reduced through verbal communication, nonverbal expressions, information seeking behaviors, self-disclosure, reciprocity, perceived similarities, and shared social networks. People also engage in plan-based message production to subtly influence others' behaviors according to their own goals.
Uncertainty Reduction Theory- Katie Corbin & Haley Sudduth- COMM 301
1) Uncertainty Reduction Theory, proposed by Charles Berger, focuses on how human communication is used to gain knowledge and reduce uncertainty in initial interactions and relationships.
2) The theory proposes that people are motivated to reduce uncertainty through communication behaviors like self-disclosure, information seeking, and developing similarities.
3) Berger developed axioms and theorems about how specific communication behaviors relate to uncertainty and influence relationship development over time. However, some aspects of the theory have been criticized or expanded on.
Uncertainty Reduction Theory G2 COMM2378
The document summarizes Uncertainty Reduction Theory, which proposes that people communicate to reduce uncertainty and discomfort when meeting strangers. It describes the theory's key aspects: (1) it identifies three strategies people use to reduce uncertainty - observing, asking others, direct communication; (2) it outlines three phases of relationships as uncertainty decreases over time; (3) it lists eight axioms about how communication and factors like intimacy, liking, and similarity impact uncertainty; (4) it discusses how theorems are derived from the axioms to make predictions. The document also notes some strengths and weaknesses of the theory and provides an example case study comparing how Koreans and Americans initially communicate to reduce uncertainty.
Uncertainty reduction theory
This document summarizes Charles Berger's Uncertainty Reduction Theory. The theory proposes that there are two types of uncertainty - behavioral and cognitive - and that people seek to reduce uncertainty about others through verbal and nonverbal communication, information seeking, self-disclosure, and focusing on similarities. It also discusses methods for coping with uncertainty, including passive, active, interactive, and hedging strategies. Finally, it briefly introduces William Gudykunst's Anxiety/Uncertainty Management Theory about how higher anxiety can lead to misunderstandings without mindful communication, especially between strangers.
Uncertainty Reduction Theory
Charles Berger's uncertainty reduction theory posits that new relationships involve uncertainty and communication aims to reduce this uncertainty. There are different types of uncertainty including behavioral and cognitive uncertainty. Berger outlines eight axioms that can be paired to produce 28 theorems about how communication reduces uncertainty. Some strategies for reducing uncertainty include seeking information from the other person directly or indirectly, choosing an appropriate level of plan complexity, and amending plans over time based on new information. However, some critiques argue that not all the axioms and theorems are valid and that uncertainty reduction may not be the sole driver of early communication between people.
Uncertainty reduction
Uncertainty reduction theory (URT) proposes that people are motivated to reduce uncertainty in interactions with others. The theory outlines seven factors that influence interpersonal exchanges, including verbal/nonverbal communication and information seeking. Higher uncertainty creates distance while nonverbal cues can help reduce it. URT describes ways people passively, actively, and interactively seek information about others to predict their behavior and feelings of uncertainty.
Social penetration theory
Social Penetration Theory describes the process of developing intimacy in relationships through mutual self-disclosure and vulnerability over time. Self-disclosure involves voluntarily sharing personal information about oneself with another and is necessary for relationships to form and communication to occur. For self-disclosure to be effective, it is important to consider the context, audience, and ensure there is reciprocation from the other person. When done properly, self-disclosure can help develop more intimate relationships and improve understanding between people.
Theory Competency #1
The Uncertainty Reduction Theory developed by Charles Berger in 1975 proposes that people seek to reduce uncertainty about a situation by gathering information about others before communicating. Berger identified eight variables related to relationship development like verbal communication, nonverbal warmth, and liking, and how they are influenced by uncertainty. Specifically, he suggested that higher uncertainty is linked to less intimacy, more information seeking and reciprocity, while lower uncertainty increases intimacy, decreases information seeking and reciprocity. Berger also identified strategies people use to reduce uncertainty like passive observation, asking others, direct interaction, and online research.
Com 103
Social Penetration Theory proposes that relationships develop from superficial to intimate levels over time through reciprocal self-disclosure. Developed in the 1960s-1970s, it assumes relationships progress in a systematic, predictable way from non-intimate to intimate through verbal and nonverbal communication. While self-disclosure allows relationships to deepen, it also increases vulnerability.
TCP - Social Judgement Theory
Social Judgment Theory proposes that people evaluate messages based on their existing attitudes. An individual's attitude has latitudes of acceptance, rejection, and non-commitment. When judging a message, one compares it to their anchor position within these latitudes. If a message falls within the latitude of acceptance, one may shift their anchor towards it; if in the latitude of rejection, one may perceive it as further than it is. The greater the discrepancy between the message and attitude, the more attitude change may occur, following a curvilinear relationship. Critics note it does not consider all persuasion factors and may not apply to clear messages.
Social Judgment Theory: What it's all about?
This powerpoint will provide a brief explanation of what the social judgment theory is and how it works.
Social Judgment Theory-Steadman
Social judgment theory predicts how persuasion will occur depending on the relationship between a message and a person's existing beliefs. If a message is closer to a person's beliefs, it will be assimilated through persuasion. If it is farther away, it will encounter contrast and fail to be persuasive. The theory also describes latitudes of acceptance, noncommitment, and rejection that determine whether a message will be assimilated or undergo contrast. Social judgment theory helps explain the role of perception in persuasion across various communication contexts like politics, public relations, and advertising.
CAPE Sociology Agnew strain theory
Robert Agnew proposed a general strain theory in 1992 that focuses on three types of strain: the failure to achieve positively valued goals, the removal of positively valued stimuli, and the presence of negative stimuli. Agnew's theory focuses on negative relationships that do not treat individuals as they expect or want to be treated, which can lead to negative emotions like anger and pressure to engage in criminal acts. While other strain theories focus on goal blockage experienced by lower classes, Agnew argues strain theory can explain crime if revised to focus on an individual's social environment, particularly for adolescents. He also suggests criminologists consider the magnitude, recency, duration, and clustering of strainful events, as well as cognitive, emotional and behavioral adaptations to
Social Judgment Theory
Social Judgment Theory proposes that people evaluate messages based on their existing attitudes or "anchor points" on issues. Messages are judged as falling within a latitude of acceptance, rejection, or non-commitment. The more ego-involved people are in an issue, the more strongly anchored and less open to persuasion their attitudes tend to be. For effective persuasion, messages need to fall just within the latitude of acceptance rather than rejection to avoid a "boomerang effect" and promote gradual attitude change over time.
Symbolic Convergence Theory
Symbolic Convergence Theory (SCT) is about sharing emotions and values through shared "fantasies" in a group. SCT was originally studied in small group communication but is now used to understand how the public views certain issues. SCT helps create bonds within groups by allowing members to work together with shared fantasies. Researchers also use SCT to gauge public reaction to topics like political races. An example of SCT in the workplace is employees sharing daydreams about after-work plans, which helps the group bond.
Comm 201 presentation
Uncertainty Reduction Theory explains that when strangers meet, they seek to reduce uncertainty about each other through various strategies like passive observation, active information seeking without direct contact, and direct interaction by asking questions and sharing information. While URT is commonly used in initial interactions and important to relationship development, its axioms and theorems have been criticized as too complex to apply practically. However, the underlying strategies for reducing uncertainty still provide value in understanding communication dynamics.
Expectancy violation theory
Expectancy Violation Theory explains how people respond to unexpected nonverbal behaviors that break social norms. How positively or negatively a violation is viewed, called valence, depends on factors like the relationship between people and cultural norms. The theory aims to understand why violations offend or please us and how to deal with unexpected changes in others' behavior. It can be applied to understand many types of interpersonal interactions.
Interpersonal Deception Theory
Interpersonal Deception Theory (IDT) proposes that deception is an interactive process between individuals rather than something determined solely by the deceiver. According to the theory, people are generally poor at detecting deception. IDT outlines common deception practices such as falsification, concealment, and equivocation. It also discusses how deceivers may exhibit unintentional nonverbal cues or "leakage" due to arousal, guilt, or cognitive overload, but that these cues are not always reliable indicators of deception. Receivers of potential deception, meanwhile, experience a dilemma in balancing their expectations of honesty with any suspicions, and indirect forms of probing a deceiver's truthfulness have uncertain value.
Symbolic convergence theory
1. Symbolic convergence theory deals with how humans interpret signs and symbols and try to unite with others they are communicating with, especially in small groups.
2. Many communication scholars utilize symbolic convergence theory to help explain human behavior through case studies of how symbols can influence behavior unconsciously.
3. Symbolic convergence theory is useful for explaining human tendencies to be influenced by symbols without realizing it, and this unconscious influence can be used in marketing and political campaigns through media.
Symbolic convergence theory
Symbolic Convergence Theory (SCT) proposes that within groups, shared emotions, motives, and meanings emerge which can develop into "fantasy chains" or depictions of events. This allows people within the group to connect through these shared understandings or fantasies, even if they do not personally know each other. SCT was developed by Ernest Bormann and suggests that communication and connections form through commonalities in how a group interprets and discusses events. While some critics argue it only applies to small groups or that shared meanings are deceptive, supporters believe SCT remains relevant and can also describe dynamics in larger organizations through common group fantasies.
My topic top five: Expectancy Violations Theory
Expectancy Violations Theory proposes that people form expectations for how others will act and react, and that violating these expectations can have consequences. The theory was created by Judee Burgoon to examine nonverbal communication expectations and violations. It suggests that understanding expectation violations can help improve relationships by providing insight into others. However, some criticism argues that aspects like self-perception of arousal may not be valid measures. Overall, the theory is best understood through specific examples of expectations being violated in interactions.
Personality traits
The document discusses personality traits, specifically the Big Five personality traits of openness, conscientiousness, extraversion, agreeableness, and neuroticism. It provides details on studies that have shown conscientiousness is valued by organizations and positively related to job performance. Agreeableness is also discussed as important for employees, but too much can lead to health issues. Extraversion is described as an important leadership trait depending on the context and individuals. The document concludes that personality traits can affect job performance.
Rumor
This document discusses rumors and their propagation. It defines rumors as unverified information that is spread from person to person, sometimes changing slightly with each retelling. The document outlines two models that describe how rumors spread through a population - the DK model involving ignorant, spreader, and stifler individuals, and the MK model involving direct contact between spreaders and others. The document also distinguishes rumors, gossip, slander, and urban legends, and discusses why rumors are spread and how to prevent their propagation.
Identifying rumours on Twitter
This document presents a research proposal for identifying rumors on Twitter. It first defines rumors as unverified information statements circulating in contexts of ambiguity or threat that help people make sense of situations and manage risk. The proposal then discusses identifying rumors based on their context, function, and content. It suggests detecting sudden increases in word frequencies and mapping word connections to identify rumor-related terms. A rumor annotation scheme is proposed that considers context, function, content and ambiguity levels. Tweets would be categorized as speculation, controversy, misinformation or disinformation using chosen measures. The goal is to better understand rumor spreading online and provide context to interpretations.
Rumour detection
This document discusses rumor detection on Facebook. It defines rumors as unverified statements that spread widely on social media. The document presents two case studies of rumors on Facebook: one about India's national anthem being named the best by UNESCO, and another that led to mob lynchings in India. It also covers related work using AI and key phrases to detect rumors, and how rumors typically spread more quickly due to limited fact-checking by users. The conclusion is that social media amplifies the spread of misinformation through rumors, which can have real-world consequences.
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
Taking AI to the Next Level in Manufacturing.pdf
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
More Related Content
What's hot
Social penetration theory
Social Penetration Theory describes the process of developing intimacy in relationships through mutual self-disclosure and vulnerability over time. Self-disclosure involves voluntarily sharing personal information about oneself with another and is necessary for relationships to form and communication to occur. For self-disclosure to be effective, it is important to consider the context, audience, and ensure there is reciprocation from the other person. When done properly, self-disclosure can help develop more intimate relationships and improve understanding between people.
Theory Competency #1
The Uncertainty Reduction Theory developed by Charles Berger in 1975 proposes that people seek to reduce uncertainty about a situation by gathering information about others before communicating. Berger identified eight variables related to relationship development like verbal communication, nonverbal warmth, and liking, and how they are influenced by uncertainty. Specifically, he suggested that higher uncertainty is linked to less intimacy, more information seeking and reciprocity, while lower uncertainty increases intimacy, decreases information seeking and reciprocity. Berger also identified strategies people use to reduce uncertainty like passive observation, asking others, direct interaction, and online research.
Com 103
Social Penetration Theory proposes that relationships develop from superficial to intimate levels over time through reciprocal self-disclosure. Developed in the 1960s-1970s, it assumes relationships progress in a systematic, predictable way from non-intimate to intimate through verbal and nonverbal communication. While self-disclosure allows relationships to deepen, it also increases vulnerability.
TCP - Social Judgement Theory
Social Judgment Theory proposes that people evaluate messages based on their existing attitudes. An individual's attitude has latitudes of acceptance, rejection, and non-commitment. When judging a message, one compares it to their anchor position within these latitudes. If a message falls within the latitude of acceptance, one may shift their anchor towards it; if in the latitude of rejection, one may perceive it as further than it is. The greater the discrepancy between the message and attitude, the more attitude change may occur, following a curvilinear relationship. Critics note it does not consider all persuasion factors and may not apply to clear messages.
Social Judgment Theory: What it's all about?
This powerpoint will provide a brief explanation of what the social judgment theory is and how it works.
Social Judgment Theory-Steadman
Social judgment theory predicts how persuasion will occur depending on the relationship between a message and a person's existing beliefs. If a message is closer to a person's beliefs, it will be assimilated through persuasion. If it is farther away, it will encounter contrast and fail to be persuasive. The theory also describes latitudes of acceptance, noncommitment, and rejection that determine whether a message will be assimilated or undergo contrast. Social judgment theory helps explain the role of perception in persuasion across various communication contexts like politics, public relations, and advertising.
CAPE Sociology Agnew strain theory
Robert Agnew proposed a general strain theory in 1992 that focuses on three types of strain: the failure to achieve positively valued goals, the removal of positively valued stimuli, and the presence of negative stimuli. Agnew's theory focuses on negative relationships that do not treat individuals as they expect or want to be treated, which can lead to negative emotions like anger and pressure to engage in criminal acts. While other strain theories focus on goal blockage experienced by lower classes, Agnew argues strain theory can explain crime if revised to focus on an individual's social environment, particularly for adolescents. He also suggests criminologists consider the magnitude, recency, duration, and clustering of strainful events, as well as cognitive, emotional and behavioral adaptations to
Social Judgment Theory
Social Judgment Theory proposes that people evaluate messages based on their existing attitudes or "anchor points" on issues. Messages are judged as falling within a latitude of acceptance, rejection, or non-commitment. The more ego-involved people are in an issue, the more strongly anchored and less open to persuasion their attitudes tend to be. For effective persuasion, messages need to fall just within the latitude of acceptance rather than rejection to avoid a "boomerang effect" and promote gradual attitude change over time.
Symbolic Convergence Theory
Symbolic Convergence Theory (SCT) is about sharing emotions and values through shared "fantasies" in a group. SCT was originally studied in small group communication but is now used to understand how the public views certain issues. SCT helps create bonds within groups by allowing members to work together with shared fantasies. Researchers also use SCT to gauge public reaction to topics like political races. An example of SCT in the workplace is employees sharing daydreams about after-work plans, which helps the group bond.
Comm 201 presentation
Uncertainty Reduction Theory explains that when strangers meet, they seek to reduce uncertainty about each other through various strategies like passive observation, active information seeking without direct contact, and direct interaction by asking questions and sharing information. While URT is commonly used in initial interactions and important to relationship development, its axioms and theorems have been criticized as too complex to apply practically. However, the underlying strategies for reducing uncertainty still provide value in understanding communication dynamics.
Expectancy violation theory
Expectancy Violation Theory explains how people respond to unexpected nonverbal behaviors that break social norms. How positively or negatively a violation is viewed, called valence, depends on factors like the relationship between people and cultural norms. The theory aims to understand why violations offend or please us and how to deal with unexpected changes in others' behavior. It can be applied to understand many types of interpersonal interactions.
Interpersonal Deception Theory
Interpersonal Deception Theory (IDT) proposes that deception is an interactive process between individuals rather than something determined solely by the deceiver. According to the theory, people are generally poor at detecting deception. IDT outlines common deception practices such as falsification, concealment, and equivocation. It also discusses how deceivers may exhibit unintentional nonverbal cues or "leakage" due to arousal, guilt, or cognitive overload, but that these cues are not always reliable indicators of deception. Receivers of potential deception, meanwhile, experience a dilemma in balancing their expectations of honesty with any suspicions, and indirect forms of probing a deceiver's truthfulness have uncertain value.
Symbolic convergence theory
1. Symbolic convergence theory deals with how humans interpret signs and symbols and try to unite with others they are communicating with, especially in small groups.
2. Many communication scholars utilize symbolic convergence theory to help explain human behavior through case studies of how symbols can influence behavior unconsciously.
3. Symbolic convergence theory is useful for explaining human tendencies to be influenced by symbols without realizing it, and this unconscious influence can be used in marketing and political campaigns through media.
Symbolic convergence theory
Symbolic Convergence Theory (SCT) proposes that within groups, shared emotions, motives, and meanings emerge which can develop into "fantasy chains" or depictions of events. This allows people within the group to connect through these shared understandings or fantasies, even if they do not personally know each other. SCT was developed by Ernest Bormann and suggests that communication and connections form through commonalities in how a group interprets and discusses events. While some critics argue it only applies to small groups or that shared meanings are deceptive, supporters believe SCT remains relevant and can also describe dynamics in larger organizations through common group fantasies.
My topic top five: Expectancy Violations Theory
Expectancy Violations Theory proposes that people form expectations for how others will act and react, and that violating these expectations can have consequences. The theory was created by Judee Burgoon to examine nonverbal communication expectations and violations. It suggests that understanding expectation violations can help improve relationships by providing insight into others. However, some criticism argues that aspects like self-perception of arousal may not be valid measures. Overall, the theory is best understood through specific examples of expectations being violated in interactions.
Personality traits
The document discusses personality traits, specifically the Big Five personality traits of openness, conscientiousness, extraversion, agreeableness, and neuroticism. It provides details on studies that have shown conscientiousness is valued by organizations and positively related to job performance. Agreeableness is also discussed as important for employees, but too much can lead to health issues. Extraversion is described as an important leadership trait depending on the context and individuals. The document concludes that personality traits can affect job performance.
Rumor
This document discusses rumors and their propagation. It defines rumors as unverified information that is spread from person to person, sometimes changing slightly with each retelling. The document outlines two models that describe how rumors spread through a population - the DK model involving ignorant, spreader, and stifler individuals, and the MK model involving direct contact between spreaders and others. The document also distinguishes rumors, gossip, slander, and urban legends, and discusses why rumors are spread and how to prevent their propagation.
Identifying rumours on Twitter
This document presents a research proposal for identifying rumors on Twitter. It first defines rumors as unverified information statements circulating in contexts of ambiguity or threat that help people make sense of situations and manage risk. The proposal then discusses identifying rumors based on their context, function, and content. It suggests detecting sudden increases in word frequencies and mapping word connections to identify rumor-related terms. A rumor annotation scheme is proposed that considers context, function, content and ambiguity levels. Tweets would be categorized as speculation, controversy, misinformation or disinformation using chosen measures. The goal is to better understand rumor spreading online and provide context to interpretations.
Rumour detection
This document discusses rumor detection on Facebook. It defines rumors as unverified statements that spread widely on social media. The document presents two case studies of rumors on Facebook: one about India's national anthem being named the best by UNESCO, and another that led to mob lynchings in India. It also covers related work using AI and key phrases to detect rumors, and how rumors typically spread more quickly due to limited fact-checking by users. The conclusion is that social media amplifies the spread of misinformation through rumors, which can have real-world consequences.
What's hot (19)
Recently uploaded
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
Taking AI to the Next Level in Manufacturing.pdf
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
A Comprehensive Guide to DeFi Development Services in 2024
DeFi represents a paradigm shift in the financial industry. Instead of relying on traditional, centralized institutions like banks, DeFi leverages blockchain technology to create a decentralized network of financial services. This means that financial transactions can occur directly between parties, without intermediaries, using smart contracts on platforms like Ethereum.
In 2024, we are witnessing an explosion of new DeFi projects and protocols, each pushing the boundaries of what’s possible in finance.
In summary, DeFi in 2024 is not just a trend; it’s a revolution that democratizes finance, enhances security and transparency, and fosters continuous innovation. As we proceed through this presentation, we'll explore the various components and services of DeFi in detail, shedding light on how they are transforming the financial landscape.
At Intelisync, we specialize in providing comprehensive DeFi development services tailored to meet the unique needs of our clients. From smart contract development to dApp creation and security audits, we ensure that your DeFi project is built with innovation, security, and scalability in mind. Trust Intelisync to guide you through the intricate landscape of decentralized finance and unlock the full potential of blockchain technology.
Ready to take your DeFi project to the next level? Partner with Intelisync for expert DeFi development services today!
System Design Case Study: Building a Scalable E-Commerce Platform - Hiike
This case study explores designing a scalable e-commerce platform, covering key requirements, system components, and best practices.
Digital Marketing Trends in 2024 | Guide for Staying Ahead
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Operating System Used by Users in day-to-day life.pptx
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
dbms calicut university B. sc Cs 4th sem.pdf
Its a seminar ppt on database management system using sql
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Programming Foundation Models with DSPy - Meetup Slides
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Choosing The Best AWS Service For Your Website + API.pptx
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Trusted Execution Environment for Decentralized Process Mining
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
Building Production Ready Search Pipelines with Spark and Milvus
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on automated letter generation for Bonterra Impact Management using Google Workspace or Microsoft 365.
Interested in deploying letter generation automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Recently uploaded (20)
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
A Comprehensive Guide to DeFi Development Services in 2024
A Comprehensive Guide to DeFi Development Services in 2024
System Design Case Study: Building a Scalable E-Commerce Platform - Hiike
System Design Case Study: Building a Scalable E-Commerce Platform - Hiike
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Operating System Used by Users in day-to-day life.pptx
Operating System Used by Users in day-to-day life.pptx
Deep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStr
Deep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStr
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
Trusted Execution Environment for Decentralized Process Mining
Trusted Execution Environment for Decentralized Process Mining
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
Theory top 5 presentation
- 1. UNCERTAINTY REDUCTION THEORY Hunter Allen
- 2. Uncertainty reduction theory is a theory that was developed by Berger and Calabrese that tries to explain how two strangers attempt to reduce uncertainty between each other during the first time they meet.
- 3. A conversation between two people is the best way for them to get to know one another. This an INTERACTIVE way for people to reduce uncertainty .
- 4. Another way of trying to get to know more about a stranger could be asking someone who already knows the stranger what they think of that person. This is an ACTIVE way for people to reduce uncertainty . “ What do you know about Jennifer? I saw her the other day, and she is really cute.” “ She goes to Clemson and she is a very nice girl, you should get to know her.”
- 5. Another way of trying to get to know someone is observing them and seeing how they act and what they do. This is a PASSIVE way of reducing uncertainty .
- 6. The Uncertainty Reduction Theory is used many ways in everyday life. Some examples of this include trying to gather information about a future professor, meeting someone in a bar, and online dating.
- 7. There are many critics of the Uncertainty Reduction Theory, who say that the theory is to assumptive, and biased.
- 8. I think it is neat how much college aged students use the Uncertainty Reduction Theory, without ever realizing they are doing so. College is a time where lifelong friendships can be made. We need to be mindful not to always assume things about people due to social media and other things before we actually meet them.