Paper presented at Wikisym 2012: Collective memories are precious resources for the society, because they help strengthening emotional bonding between community members, maintaining groups cohesion, and directing future behavior. Studying how people form their collective memories of emotional upheavals is important in order to better understand people's reactions and the consequences on their psychological health. Previous research investigated the effects of single traumatizing events, but few of them tried to compare different types of traumatic events like natural and man-made disasters. In this paper, interpreting Wikipedia as a collective memory place, we compare articles about natural and human-made disasters employing automated natural language techniques, in order to highlight the different psychological processes underlying users' sensemaking activities.
Holocaust History Detectives - Names and Memorials Teacher GuideH2D_Tutorials
The "Mining Information from Multimedia Sources - Holocaust History Detectives" (MIMS-H2D) project applies a crowdsourcing strategy to engage students and adults in helping to recover the names of Holocaust victims. The project utilizes a variety of primary sources of witness testimony and databases to engage participants in contributing to the historical record and honoring the memory of those who were killed. This learning module is designed to engage students in understanding the processes and challenges associated with recovering the names of Holocaust victims.
Registration is required for complete access to additional resource materials and to participate in the project. Visit www.theYIZKORproject.org/home.htm to register
Collective Memory building in Wikipedia: the case of North African uprisingsPaolo Massa
Paper presented at Wikisym 2011, 7th International Symposium on Wikis and Open Collaboration
Read the paper at http://www.gnuband.org/papers/collective_memory_building_in_wikipedia_the_case_of_north_african_uprisings/
Authors: Michela Ferron, Paolo Massa
Abstract:
Since December 2010, a series of protests and uprisings have shocked North African countries such as Tunisia, Egypt, Libya, Syria, Yemen and more. In this paper, focusing mainly on the Egyptian revolution, we provide evidence of the intense edit activity occurred during these uprisings on the related Wikipedia
pages. Thousands of people provided their contribution on the content pages and discussed improvements and disagreements on the associated talk pages as the traumatic events unfolded. We
propose to interpret this phenomenon as a process of collective memory building and argue how on Wikipedia this can be studied empirically and quantitatively in real time. We explore and suggest possible directions for future research on collective memory formation of traumatic and controversial events in Wikipedia.
Coordinating Human and Machine Intelligence to Classify Microblog Communica0o...Muhammad Imran
An emerging paradigm for the processing of data streams involves human and machine computation working together, allowing human intelligence to process large-scale data. We apply this approach to the classification of crisis-related messages in microblog streams. We begin by describing the platform AIDR (Artificial Intelligence for Disaster Response), which collects human annotations over time to create and maintain automatic supervised classifiers for social media messages. Next, we study two significant challenges in its design: (1) identifying which elements must be labeled by humans, and (2) determining when to ask for such annotations to be done. The first challenge is selecting the items to be labeled by crowdsourcing workers to maximize the productivity of their work. The second challenge is to schedule the work in order to reliably maintain high classification accuracy over time. We provide and validate answers to these challenges by extensive experimentation on real- world datasets.
This is a presentation I created to introduce myself to the 2012 group of high schoolers in the Museum of Science and Industry's Science Achievers program.
Holocaust History Detectives - Names and Memorials Teacher GuideH2D_Tutorials
The "Mining Information from Multimedia Sources - Holocaust History Detectives" (MIMS-H2D) project applies a crowdsourcing strategy to engage students and adults in helping to recover the names of Holocaust victims. The project utilizes a variety of primary sources of witness testimony and databases to engage participants in contributing to the historical record and honoring the memory of those who were killed. This learning module is designed to engage students in understanding the processes and challenges associated with recovering the names of Holocaust victims.
Registration is required for complete access to additional resource materials and to participate in the project. Visit www.theYIZKORproject.org/home.htm to register
Collective Memory building in Wikipedia: the case of North African uprisingsPaolo Massa
Paper presented at Wikisym 2011, 7th International Symposium on Wikis and Open Collaboration
Read the paper at http://www.gnuband.org/papers/collective_memory_building_in_wikipedia_the_case_of_north_african_uprisings/
Authors: Michela Ferron, Paolo Massa
Abstract:
Since December 2010, a series of protests and uprisings have shocked North African countries such as Tunisia, Egypt, Libya, Syria, Yemen and more. In this paper, focusing mainly on the Egyptian revolution, we provide evidence of the intense edit activity occurred during these uprisings on the related Wikipedia
pages. Thousands of people provided their contribution on the content pages and discussed improvements and disagreements on the associated talk pages as the traumatic events unfolded. We
propose to interpret this phenomenon as a process of collective memory building and argue how on Wikipedia this can be studied empirically and quantitatively in real time. We explore and suggest possible directions for future research on collective memory formation of traumatic and controversial events in Wikipedia.
Coordinating Human and Machine Intelligence to Classify Microblog Communica0o...Muhammad Imran
An emerging paradigm for the processing of data streams involves human and machine computation working together, allowing human intelligence to process large-scale data. We apply this approach to the classification of crisis-related messages in microblog streams. We begin by describing the platform AIDR (Artificial Intelligence for Disaster Response), which collects human annotations over time to create and maintain automatic supervised classifiers for social media messages. Next, we study two significant challenges in its design: (1) identifying which elements must be labeled by humans, and (2) determining when to ask for such annotations to be done. The first challenge is selecting the items to be labeled by crowdsourcing workers to maximize the productivity of their work. The second challenge is to schedule the work in order to reliably maintain high classification accuracy over time. We provide and validate answers to these challenges by extensive experimentation on real- world datasets.
This is a presentation I created to introduce myself to the 2012 group of high schoolers in the Museum of Science and Industry's Science Achievers program.
(note: many animations do not replicated in SlideShare; it is suggested that you view in the native PowerPoint program)
Week One – “A History of Media Psychology”, which will feature discussion of the early “moral panic” days of research, including The Payne Fund Studies, The Seduction of the Innocent, and a discussion of the psychological underpinnings of the infamous War of the Worlds broadcast. Our discussion this week will also include an overview of the history of leisure and it’s relation (positive and negative) to society.
Power Point that accompanies my talk, To Perform a Theory of Feminist Digital Praxis: Cutting Through the Noise of the Digital Self, Noise Seminar, Utrecht, August 27, 2014
Face Ex Machina. Demiurgical Faces from the Eye of Hal9000 to S1m0ne and AvaFACETSERC
Bruno Surace, video of the conference: https://www.youtube.com/watch?v=nGK55-6wj2I&t=1028s
"Transhuman Visages: Artificial Faces in Arts, Science, and Society", Symposium and Meeting of the Senior Advisory Board, PIAST, Polish Institute of Advanced Studies, 28 January 2020
Kane, G. (2009). It’s a Network,Not an Encyclopedia: A Social Network Perspective on Wikipedia Collaboration. Academy of Management Annual Meeting Proceedings.
The Internet is full of Web Services, everyday more and more. Some services offer API (application programming interface) that developers use to build new applications (mash-ups). One of the most known and used technology for the machine-to-machine communication is SOAP (Simple Object Access Protocol) but in the last years we can use another paradigm, ReST (Representational State Transfer). How does it work?
This is the presentation to the LiveMemories partners of our joint work on the case study and proposed first showcase for the project. The case study is directed to the San Bartolameo Students Residence and district (south of Trento, Italy), and it is being carried on in collaboration with Opera Universitaria, Portobeseno, Studiare a Trento, and Cooperativa Mercurio.
(note: many animations do not replicated in SlideShare; it is suggested that you view in the native PowerPoint program)
Week One – “A History of Media Psychology”, which will feature discussion of the early “moral panic” days of research, including The Payne Fund Studies, The Seduction of the Innocent, and a discussion of the psychological underpinnings of the infamous War of the Worlds broadcast. Our discussion this week will also include an overview of the history of leisure and it’s relation (positive and negative) to society.
Power Point that accompanies my talk, To Perform a Theory of Feminist Digital Praxis: Cutting Through the Noise of the Digital Self, Noise Seminar, Utrecht, August 27, 2014
Face Ex Machina. Demiurgical Faces from the Eye of Hal9000 to S1m0ne and AvaFACETSERC
Bruno Surace, video of the conference: https://www.youtube.com/watch?v=nGK55-6wj2I&t=1028s
"Transhuman Visages: Artificial Faces in Arts, Science, and Society", Symposium and Meeting of the Senior Advisory Board, PIAST, Polish Institute of Advanced Studies, 28 January 2020
Kane, G. (2009). It’s a Network,Not an Encyclopedia: A Social Network Perspective on Wikipedia Collaboration. Academy of Management Annual Meeting Proceedings.
The Internet is full of Web Services, everyday more and more. Some services offer API (application programming interface) that developers use to build new applications (mash-ups). One of the most known and used technology for the machine-to-machine communication is SOAP (Simple Object Access Protocol) but in the last years we can use another paradigm, ReST (Representational State Transfer). How does it work?
This is the presentation to the LiveMemories partners of our joint work on the case study and proposed first showcase for the project. The case study is directed to the San Bartolameo Students Residence and district (south of Trento, Italy), and it is being carried on in collaboration with Opera Universitaria, Portobeseno, Studiare a Trento, and Cooperativa Mercurio.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
Psychological processes underlying Wikipedia representations of natural and manmade disasters
1. Psychological processes underlying
Wikipedia representations of
natural and manmade disasters
Michela Ferron Paolo Massa
Center for Mind/Brain Sciences Fondazione
University of Trento Bruno Kessler
m.ferron@unitn.it massa@fbk.eu
2.
3. Anti-Islamic
hate crimes
after 9/11
movies
Legislation &
surveillance
4. Outline
Collective Memories
Wikipedia as a global memory place
Automated natural language techniques
Traumatic VS Non traumatic events
Old VS recent traumatic events
Traumatic events caused by man VS nature
Conclusions
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
5. Collective Memories
A set of ideas, images, feelings about the past, built
through an active process of sense-making through time
Memorial
Lincoln to the
memorial murdered
Jews of
Europe
Wahington Ocklaoma
memorial City
bombings
memorial
Photos: Wikipedia (1, 2, 3, 4)
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
6. Traumatic events
September 11 attacks 2005 London bombings
2004 IndianTsunami Kennedy
assassination
Photos: Wikipedia (1, 2) and Flickr (3,
4)
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
7. Traumatic events
short-term and long-term effects
After a traumatic event: Collective memories:
Anti-Islamic
hate crimes
Violence increases Maintain social bonds
after 9/11
(Pennebaker and Harber, 1993; FBI national hate crime statistics) (Wang, 2008; Irwin-Zarecka, 1994)
Psychological/health problems
increase of negative emotions Direct behavior
(Wang, 2008; Pennebaker et al., 1997; Irwin-Zarecka, 1994)
(Koss & Kilpatrick, 2001; Stroebe, Hansson, Stroebe, & Schut,
2001)
increase of cognitive activity Are persistent for years and
(Davis & Nolen-Hoeksema, 2001; Pennebaker et al., 2003) can be at the root of wars,
increase of social sharing and prejudice, cultural identities
social support (Pennebaker et al., 1997)
(Mehl & Pennebaker, 2003; Pyszczynski, Solomon, & Greenberg,
2002; Rimé et al.,1998)
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
8. Wikipedia as a global memory place
What happens in Wikipedia
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
9. Wikipedia as a global memory place
“[…] the online encyclopaedia is a global memory place
where locally disconnected participants can express and
debate divergent points of view and that this leads to the
formation and ratification of shared knowledge that
constitutes collective memory.”
(Pentzold, 2009, p. 263)
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
10. Automated natural language
processing techniques
Goal: to analyze the content of Wikipedia articles about
natural and man-made disasters employing automated
content analysis tools
Linguistic Inquiry & Word Count (Pennebaker et al., 2001)
searches for words across:
Linguistic categories (e.g. pronouns, articles, tenses)
Psychological categories (e.g. social, affective, cognitive processes)
Traumatic VS non traumatic events
Temporal focus of old VS recent events
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
11. Traumatic and non traumatic events
Hypotheses
Psychological processes Examples
Affective processes Happy, hate, kiss
Positive emotions Love, party, pleasant
Negative emotions Hurt, abuse, scary
Anxiety Worried, afraid
LIWC to get a score Anger Kill, aggression, destroy
Sadness Sad, cry, depression
for each psychological Cognitive processes Cause, acknowledge, admit
variable Insight Think, assume, interpret
Causation Because, depend, elicit
Discrepancy Should, could, if
Tentative Maybe, apparently, suppose
Certainty Always, absolutely, clear
Inhibition Block, abstain, avoid
Inclusive And, add, along
Exclusive But, either, without
Social processes Mate, guy, boy
Family Daughter, brother, dad
Friends Buddy, friend, mate
Humans Adult, children, girl
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
12. Traumatic and non traumatic events
Data
Wikipedia’s categories (“Events by topic”), History
Central and Information Britain
66 articles about traumatic events (e.g. September 11
attacks, 7 July 2005 London bombings, Chernobyl disaster)
40 articles about non traumatic events (e.g.
Coronation of Queen Elizabeth II, Woodstock Festival, Super
Bowl XXXVIII)
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
13. Traumatic and non traumatic events
Hypotheses
Psychological processes Examples
Affective processes Happy, hate, kiss
Positive emotions Love, party, pleasant
Higher presence in articles Negative emotions Hurt, abuse, scary
about traumatic events of: Anxiety
Anger
Worried, afraid
Kill, aggression, destroy
negative emotions Sadness Sad, cry, depression
Cognitive processes Cause, acknowledge, admit
cognitive processes Insight Think, assume, interpret
social processes Causation Because, depend, elicit
Discrepancy Should, could, if
Tentative Maybe, apparently, suppose
Certainty Always, absolutely, clear
Inhibition Block, abstain, avoid
In articles about non Inclusive
Exclusive
And, add, along
But, either, without
traumatic events: Social processes Mate, guy, boy
positive emotions Family Daughter, brother, dad
Friends Buddy, friend, mate
Humans Adult, children, girl
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
14. Traumatic and non traumatic events
Analysis
1 negative emotion
14 total words
negative emotions
Arcsine transformation
T-tests for indipendent samples
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
15. Traumatic and non traumatic events
Results
All differences in the graphs
are statistically significant
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
16. Temporal focus of old and recent
traumatic events: Data & Analysis
Articles in their early stage (after 500 revisions)
Temporal focus more evident
Many words per article
Out of 55 articles
26 about events happened before 2001 (e.g. John F. Kennedy
assassination)
29 about events happened after 2001 (e.g. 2011 Tohoku
earthquake and tsunami)
LIWC: linguistics categories (past, present and future tenses)
Arcsine transformation and t-tests for independent samples
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
17. Temporal focus of old and recent traumatic
events: Hypotheses & Results
HP: higher presence of past tense in old events, higher
presence of present/future tenses in recent events
*
*
*
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
18. LIWC applied to Wikipedia
LIWC is effective in detecting
Differences in content referred to psychological processes
emerging from articles about traumatic and non traumatic
events
Differences in the temporal focus of articles about old and
recent traumatic events
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
19. Natural and human-made
traumatic events
How people remember traumatic events:
Understand the consequences on the physical and
psychological health of people and communities
Differences in the psychological processes:
First step toward the understanding and the prediction of
trauma, typical responses to it, and short and long-term effects
Empirically validate theoretical findings in Wikipedia
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
20. Natural and human-made
traumatic events
Traumatic events can be very different
Theoretical reasons to distinguish between natural and
human-made traumatic events
Literature: human accidents may have longer and more
insidious effects of physical and psychological health:
negative emotions; nervousness and anxiety (Cohn et al., 2004; Adler, 1943)
psychological and work-related problems (Leopold and Dillon, 1963; Henderson
and Bostock, 1977; Ploeger, 1972)
depression, anxiety, personality changes (Titchener and Kapp, 1976)
sleep disturbances and psychiatric problems (Gleser et al., 1981; Gleser et al.,
1978)
war-related dreams and aggravated assaults (Pennebaker and Harber, 1993)
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
21. Natural and human-made
traumatic events
Natural disasters Human disasters
Uncontrollable Loss of control
helplessness stress arousal
2004 IndianTsunami September 11 attacks
Baum et al., 1986
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
22. Natural and human-made traumatic events
Data
Articles in their early stage (after 500 revisions)
Out of 55 articles with at least 500 revisions
36 about events caused by man (e.g. “Fort Hood shooting”,
“2011 Norway attacks”)
Wikipedia’s categories, e.g. “Assassinations”, “Terrorist incidents”
19 about events caused by nature (e.g. “2004 Indian Ocean
earthquake and tsunami”, “2010 Haiti earthquake”)
Wikipedia’s categories, e.g. “2008 Atlantic Hurricane Season”, “1993
natural disasters”
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
23. Natural and human-made traumatic events
Hypotheses
Affective processes
Human-made disasters: loss of control (distress) higher anxiety,
anger
Natural disasters: uncontrollable (helplessness) higher sadness
Cognitive processes
Human-made disasters: loss of control higher cognitive processes
Social processes
Human-made disasters: increased orientation toward others + more
references to people higher social processes
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
24. Natural and human-made traumatic events
Results
* Human-made
*
traumatic events:
* more anxiety,
anger (blame)
Natural disasters:
more sadness
Affective processes Happy, hate, kiss (passive behavior)
Positive emotions Love, party, pleasant
Negative emotions Hurt, abuse, scary
Anxiety Worried, afraid
Anger Kill, aggression, destroy
Sadness Sad, cry, depression
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
25. Natural and human-made traumatic events
Results
Human-made
*
traumatic events:
need for
explanation is
* critical (unexpected
* *
loss of control)
Natural disasters:
Cognitive processes Cause, acknowledge, admit need for
Insight Think, assume, interpret
Causation Because, depend, elicit
explanation is less
Discrepancy Should, could, if pressing (nature is
Tentative Maybe, apparently, suppose uncontrollable)
Certainty Always, absolutely, clear
Inhibition Block, abstain, avoid
Inclusive And, add, along
Exclusive But, either, without
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
26. Natural and human-made traumatic events
Results
* Human-made
traumatic events:
higher social
orientation?
* more references
to people
(bomber’s family
or social relations)
Social processes Mate, guy, boy
Family Daughter, brother, dad
Friends Buddy, friend, mate
Humans Adult, children, girl
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
27. Considerations
Difficult definition of human-made and natural disasters
Wikipedia’s categories
But the distinction is not always clear-cut (“2011 Tōhoku
earthquake and tsunami”)
LIWC and other automated techniques
Limitations (psychological categories are subjective and
context-dependent)
Know your data (noise caused by bots, vandalism, templates)
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
28. Conclusions: Take-home message
Different psychological and sensemaking processes
underlying users editing activity
Specific patterns of emotional language
Arousal
stressful high
focused anger Man-made disasters activation
anger, anxiety
heavier effects
negative positive
Valence
passive responses Natural disasters
sadness
low
activation
Background Wikipedia LIWC Traum. - non traum. Old - recent Man - Nature Conclusions
A set of ideas and feelings about the past, built through discussion, public ceremonies, memorials (1) Lincoln memorial, (2) Jews, (3) Ocklaoma City bombings, (4) Washington memorial.
Because: - social sharing - increase of violence - psychological + health problems - good perspective for the study of collective memory processes - literature on cultural trauma research (trauma as cultural process)
This assumption is drawn from Halbwachs’s notion of collective memory (social function of memory: people feel united through the construction of a common past), the Assmanns’ discussion of communicative and cultural memory (everyday communication, interactive, informal VS objective, formal, well organized ), Nora’s memory places (any entity which has become a symbolic element of the memory heritage of a community) and Vansina’s ‘floating gap’ model (as the time goes by recent past – expressed in interactive communication - goes into the background, fading).