SlideShare a Scribd company logo
1 of 33
Download to read offline
“Concise Preservation by Combining Managed Forgetting
and Contextualized Remembering”
EU/FP7 ForgetIT Project (2013-2016)
http://www.forgetit-project.eu
What Triggers Human Remembering of Events?
Large-Scale Analysis of Collective Memory in Wikipedia
Nattiya Kanhabua, Tu Ngoc Nguyen and Claudia Niederée
L3S Research Center , Hannover, Germany
Motivation: ForgetIT Project
Human Forgetting and Remembering
Collective Memory in Wikipedia
Experiments and Discussion
Conclusions
Outline
However, we are facing:
• Dramatic increase in content creation (e.g. digital photos)
• Increasing use of mobile devices with restricted capacity
• Information overload and changing professional and private lives
• Inadvertent forgetting due to lack of systematic preservation
Forgetting plays a crucial role for human remembering and life
(focus on current, relevant information; ignore redundant details)
Managed forgetting ≠ automatic deletion
Instead: a range of forgetting options e.g.
• Resource condensation
• Change of indexing & ranking
• Reduction of redundancy
A computer that forgets intentionally ?
And, in context of digital preservation??
However, we are facing:
• Dramatic increase in content creation (e.g. digital photos)
• Increasing use of mobile devices with restricted capacity
• Information overload and changing professional and private lives
• Inadvertent forgetting due to lack of systematic preservation
Forgetting plays a crucial role for human remembering and life
(focus on current, relevant information; ignore redundant details)
Managed forgetting ≠ automatic deletion
Instead: a range of forgetting options e.g.
• Resource condensation
• Change of indexing & ranking
• Reduction of redundancy
A computer that forgets intentionally ?
And, in context of digital preservation??
Managed forgetting = to remember the right information
Individual memories are subject to a fast
forgetting process [Ebbinghaus, 1885]
• Rapidly forget details -> “less redundancy”
Episodic memory (of one’s past event) is
reconstructed from similar events/context
• Rely on common patterns -> “false memory”
Memory bumps in the forgetting curve is
caused by reminding or triggering of:
• A physical object (e.g. a printed photo)
• A digital memory system
• Different subsequent events
Human Forgetting and Remembering
H. Ebbinghaus, Über das Gedächtnis. Untersuchungen zur experimentellen Psychologie. Duncker & Humblot,
Leipzig, 1885.
E. Tulving, Episodic memory: From mind to brain. Annual review of psychology, vol. 53, no. 1, pp. 1-25, 2002.
“ Collective memory is a socially constructed, common image (memory)
of the past of a community, which frames its current understanding
and actions.” [Halbwachs, 1950]
• Crowd phenomenon and important to societal processes
• Not static as determined by the concerns of the present
From Individual Memories to Collective Memory
M. Halbwachs, On collective memory. Chicago: The University of Chicago Press, 1950 (Translation).
Flashbulb memories in cognitive psychology
• A study of remembering of high-impact events, e.g.,
The British Royal Wedding or September 11 attacks
• Aspects: details, confidence, consistency of memory
over time, impact of media coverage
• Qualitative study: limited number of events and users
Collective Memory in Wikipedia
Wikipedia as a source for global memory
• Largest and most up-to-date online encyclopedia
(19M registered users, 30K active editors)
• Social negotiation and construction reflected in
early editing activities and talk pages
• Indicators for identifying real-world events
C. Pentzold, The online encyclopaedia wikipedia as a global memory place, Memory Studies, 2009.
M. Georgescu, N. Kanhabua, D. Krause, W. Nejdl, and S. Siersdorfer, Extracting event-related information
from article updates in wikipedia, ECIR'2013.
View logs as the signal for collective memory
• Public page view traffics with a long time span
• Not directly reflect how people forget; significant
patterns are a good estimate public remembering
• Large-scale analysis complements (1) qualitative
studies (2) analyzing article content (scalability)
Contributions
First study of identifying catalysts for event memory triggering by using
time series analysis techniques:
• temporal correlations in peaking page visits between events,
• a surprise score or the residual sum of squares on prediction error, and
• the skewness of view shapes as a catalyst for memories
Identify the relationship between events by using different features
• the role of time passed, the same types of events, the size or magnitude of
events, the near-by city or neighbor country
Analyze over 5500 high-impact events from 11 event categories
Related to the previous study by [Au Yeung and Jatowt, 2011]
• Analyzed references to the past (as an indicator to what is remembered) in a
large news collection for identifying, which years are most frequently referenced
C.-m. Au Yeung and A. Jatowt, Studying how the past is remembered: Towards computational history
through large scale text mining, CIKM’2011
We propose a 3-step approach, for a given event:
1. Compute “remembering scores” of past events within the same category
2. Rank related past events by the computed remembering scores
3. Identify features (e.g., time, location) having a high correlation with remembering
Our Approach
Remembering scores: a linear
combination of three features:
1. Cross-correlation coefficient (CCF)
2. Sum of squared error (SSE)
3. Skewness (Kurtosis)
Measuring Signals for Memory Revival
Remembering scores: a linear
combination of three features:
1. Cross-correlation coefficient (CCF)
2. Sum of squared error (SSE)
3. Skewness (Kurtosis)
Measuring Signals for Memory Revival
Remembering scores: a linear
combination of three features:
1. Cross-correlation coefficient (CCF)
2. Sum of squared error (SSE)
3. Skewness (Kurtosis)
Measuring Signals for Memory Revival
Remembering = α•CCF + β•SSE + γ•Kurtosis
Features for Triggered Remembering
Temporal similarity:
• Time distance between two events (in days, months or years)
• Time distance based on exponential decay functions
Location similarity:
• Map a geographic hierarchy of event locations as follows
 city -> state -> country -> neighbor countries -> continent
• Assign 4 scale values: 4 to same city, 3 to state, 2 to country,1 to continent
Impact of Events:
• Damaged area/properties/cost/fatalities
• Magnitude (for earthquake events)
• Highest winds, lowest pressure (for Atlantic hurricanes)
N. Kanhabua and K. Nørvåg: Determining time of queries for re-ranking search results. ECDL 2010
J. Strötgen, M. Gertz, and C. Junghans: An event-centric model for multilingual document similarity. SIGIR 2011
Experiments
Datasets:
• Page views statistics 2007-2013
• A large set of 5,500 events
• From 11 event-related categories
• α = 0.5, β = 0.4, γ = 0.1
Temporal and spatial distributions
• Strong focus on more recent events
• Better coverage with increasing popularity
• Most frequent locations depending on event types
Temporal and Spatial Distributions
Temporal and spatial distributions
• Strong focus on more recent events
• Better coverage with increasing popularity
• Most frequent locations depending on event types
Temporal and Spatial Distributions
Temporal and spatial distributions
• Strong focus on more recent events
• Better coverage with increasing popularity
• Most frequent locations depending on event types
Temporal and Spatial Distributions
Category: Atlantic Hurricane
Distributions of remembering scores
• Hurricane Sandy (Form date: October 22, 2012, Affected area: Mid-Atlantic)
• Hurricane Hanna (Form date: August 28, 2008, Affected area: US east coast)
Category: Atlantic Hurricane
Distributions of remembering scores
• Hurricane Sandy (Form date: October 22, 2012, Affected area: Mid-Atlantic)
• Hurricane Hanna (Form date: August 28, 2008, Affected area: US east coast)
Location and time have a low effect on
remembering scores for this category.
Category: Atlantic Hurricane
Top-10 events triggered by the two events
• Hurricane Hanna commemorates Hurricane Gustav, the freshest hurricane
stuck at the area of Puerto Rico and East Coast
• Hurricane Sandy triggers 1991 Perfect Storm initially formed around Canada
area, which t is high impact and most destructive
Category: Atlantic Hurricane
Top-10 events triggered by the two events
• Hurricane Hanna commemorates Hurricane Gustav, the freshest hurricane
stuck at the area of Puerto Rico and East Coast
• Hurricane Sandy triggers 1991 Perfect Storm initially formed around Canada
area, which t is high impact and most destructive
Category: Aviation accidents
Mixture of impact factors, such as, time and location
• Qantas Flight 32 (crashed on 4 November 2010) triggers remembering of
(1) Qantas Flight 30 and British Airways Flight 9 (both going to Australia),
and (2) Aero Caribbean Flight 883 (most recent event)
Most recent
Category: Aviation accidents
Mixture of impact factors, such as, time and location
• Qantas Flight 32 (crashed on 4 November 2010) triggers remembering of
(1) Qantas Flight 30 and British Airways Flight 9 (both going to Australia),
and (2) Aero Caribbean Flight 883 (most recent event)
Same
destination
Category: Aviation accidents
Mixture of impact factors, such as, time and location
• Qantas Flight 32 (crashed on 4 November 2010) triggers remembering of
(1) Qantas Flight 30 and British Airways Flight 9 (both going to Australia),
and (2) Aero Caribbean Flight 883 (most recent event)
Same
destination
Deadliest (two
aircraft collided)
Concorde
Category: Earthquakes
A series of earthquake events at Christchurch, New Zealand
• 2010 Canterbury earthquake triggers 2010 Haiti earthquake (recent and high-
impact) and two close-by events, and high-impact historical earthquakes
• 2011 Christchurch earthquake shows locality focus, i.e., people seem to be
interested in the previous events in the same region
• June 2011 Christchurch earthquake, the remembered events are dominated
by the two predecessor events
Category: Earthquakes
A series of earthquake events at Christchurch, New Zealand
• 2010 Canterbury earthquake triggers 2010 Haiti earthquake (recent and high-
impact) and two close-by events, and high-impact historical earthquakes
• 2011 Christchurch earthquake shows locality focus, i.e., people seem to be
interested in the previous events in the same region
• June 2011 Christchurch earthquake, the remembered events are dominated
by the two predecessor events
Category: Earthquakes
A series of earthquake events at Christchurch, New Zealand
• 2010 Canterbury earthquake triggers 2010 Haiti earthquake (recent and high-
impact) and two close-by events, and high-impact historical earthquakes
• 2011 Christchurch earthquake shows locality focus, i.e., people seem to be
interested in the previous events in the same region
• June 2011 Christchurch earthquake, the remembered events are dominated
by the two predecessor events
Category: Earthquakes
A series of earthquake events at Christchurch, New Zealand
• 2010 Canterbury earthquake triggers 2010 Haiti earthquake (recent and high-
impact) and two close-by events, and high-impact historical earthquakes
• 2011 Christchurch earthquake shows locality focus, i.e., people seem to be
interested in the previous events in the same region
• June 2011 Christchurch earthquake, the remembered events are dominated
by the two predecessor events
Look beyond single events, especially, if there are
several events in temporal and local proximity.
Category: Earthquakes
A series of earthquake events at Christchurch, New Zealand
• 2010 Canterbury earthquake triggers 2010 Haiti earthquake (recent and high-
impact) and two close-by events, and high-impact historical earthquakes
• 2011 Christchurch earthquake shows locality focus, i.e., people seem to be
interested in the previous events in the same region
• June 2011 Christchurch earthquake, the remembered events are dominated
by the two predecessor events
Look beyond single events, especially, if there are
several events in temporal and local proximity.
Category: Terrorist incidents
Interesting observation: semantic similarity between events
• June 2012 Kaduna church bombings triggers other religion terror attacks
• 2008 Mumbai attacks trigger terror attacks in business, entertainment and hotels
2nd
5th
24th
Category: Terrorist incidents
Interesting observation: semantic similarity between events
• June 2012 Kaduna church bombings triggers other religion terror attacks
• 2008 Mumbai attacks trigger terror attacks in business, entertainment and hotels
2nd
7th
15th
Conclusions
We identified some first pattern for event memory triggering for diverse
event types including natural and manmade disasters as well as
accidents and terrorism.
Our analysis confirmed the influence of closeness in time and location,
but the semantic similarity of events also influences which event
memories are triggered by an event.
In our future work, we plan to deepen our systematic analysis of factors
for revisiting past events and of the combination of those factors.
We also plan to investigate external factors such as media coverage
linking new events to past events or reflection of such relationships in
other types of social media.
What do you remember?
Thanks for your attention!

More Related Content

Similar to Combining Managed Forgetting and Contextualized Remembering

Temporal models for mining, ranking and recommendation in the Web
Temporal models for mining, ranking and recommendation in the WebTemporal models for mining, ranking and recommendation in the Web
Temporal models for mining, ranking and recommendation in the WebTu Nguyen
 
From Archives to Climate Science
From Archives to Climate ScienceFrom Archives to Climate Science
From Archives to Climate Sciencelifeofdata
 
Media frames and Memory: Social constructions of climate change following the...
Media frames and Memory: Social constructions of climate change following the...Media frames and Memory: Social constructions of climate change following the...
Media frames and Memory: Social constructions of climate change following the...Erin Bohensky
 
20120821 putting the world’s cultural heritage online with crowd sourcing [na...
20120821 putting the world’s cultural heritage online with crowd sourcing [na...20120821 putting the world’s cultural heritage online with crowd sourcing [na...
20120821 putting the world’s cultural heritage online with crowd sourcing [na...Frederick Zarndt
 
Cytora: Real-Time Political Risk Analysis
Cytora:  Real-Time Political Risk AnalysisCytora:  Real-Time Political Risk Analysis
Cytora: Real-Time Political Risk Analysishuguk
 
Archiving news on the Web through RSS flows. A new tool for studying interna...
Archiving news on the Web through RSS flows. A new tool for studying interna...Archiving news on the Web through RSS flows. A new tool for studying interna...
Archiving news on the Web through RSS flows. A new tool for studying interna...Marta Severo
 
AHRC Digital Transformations theme: the Story So Far
AHRC Digital Transformations theme: the Story So FarAHRC Digital Transformations theme: the Story So Far
AHRC Digital Transformations theme: the Story So FarAndrew Prescott
 
Projects2012
Projects2012Projects2012
Projects2012jarising
 
Fifty shades of evidence: A transdisciplinary research project on changing cl...
Fifty shades of evidence: A transdisciplinary research project on changing cl...Fifty shades of evidence: A transdisciplinary research project on changing cl...
Fifty shades of evidence: A transdisciplinary research project on changing cl...Carina van Rooyen
 
Essay On Library Museum And Archive
Essay On Library Museum And ArchiveEssay On Library Museum And Archive
Essay On Library Museum And ArchiveJessica Rinehart
 
Searching over the past, present and future
Searching over the past, present and futureSearching over the past, present and future
Searching over the past, present and futureRoi Blanco
 
Participant Observation Lecture
Participant Observation LectureParticipant Observation Lecture
Participant Observation LectureMichael Palkowski
 
Big Data in the Arts and Humanities: Stirling presentation
Big Data in the Arts and Humanities: Stirling presentationBig Data in the Arts and Humanities: Stirling presentation
Big Data in the Arts and Humanities: Stirling presentationAndrew Prescott
 

Similar to Combining Managed Forgetting and Contextualized Remembering (20)

Temporal models for mining, ranking and recommendation in the Web
Temporal models for mining, ranking and recommendation in the WebTemporal models for mining, ranking and recommendation in the Web
Temporal models for mining, ranking and recommendation in the Web
 
Unit 1 Introductory Presentation
Unit 1 Introductory PresentationUnit 1 Introductory Presentation
Unit 1 Introductory Presentation
 
From Archives to Climate Science
From Archives to Climate ScienceFrom Archives to Climate Science
From Archives to Climate Science
 
Herring Noaa Spring08
Herring Noaa Spring08Herring Noaa Spring08
Herring Noaa Spring08
 
Media frames and Memory: Social constructions of climate change following the...
Media frames and Memory: Social constructions of climate change following the...Media frames and Memory: Social constructions of climate change following the...
Media frames and Memory: Social constructions of climate change following the...
 
20120821 putting the world’s cultural heritage online with crowd sourcing [na...
20120821 putting the world’s cultural heritage online with crowd sourcing [na...20120821 putting the world’s cultural heritage online with crowd sourcing [na...
20120821 putting the world’s cultural heritage online with crowd sourcing [na...
 
Cytora: Real-Time Political Risk Analysis
Cytora:  Real-Time Political Risk AnalysisCytora:  Real-Time Political Risk Analysis
Cytora: Real-Time Political Risk Analysis
 
Weather Headlines
Weather HeadlinesWeather Headlines
Weather Headlines
 
Archiving news on the Web through RSS flows. A new tool for studying interna...
Archiving news on the Web through RSS flows. A new tool for studying interna...Archiving news on the Web through RSS flows. A new tool for studying interna...
Archiving news on the Web through RSS flows. A new tool for studying interna...
 
Does keyword noise change over space and time? A case study of flood- and rai...
Does keyword noise change over space and time? A case study of flood- and rai...Does keyword noise change over space and time? A case study of flood- and rai...
Does keyword noise change over space and time? A case study of flood- and rai...
 
AHRC Digital Transformations theme: the Story So Far
AHRC Digital Transformations theme: the Story So FarAHRC Digital Transformations theme: the Story So Far
AHRC Digital Transformations theme: the Story So Far
 
Projects2012
Projects2012Projects2012
Projects2012
 
Fifty shades of evidence: A transdisciplinary research project on changing cl...
Fifty shades of evidence: A transdisciplinary research project on changing cl...Fifty shades of evidence: A transdisciplinary research project on changing cl...
Fifty shades of evidence: A transdisciplinary research project on changing cl...
 
Essay On Library Museum And Archive
Essay On Library Museum And ArchiveEssay On Library Museum And Archive
Essay On Library Museum And Archive
 
Searching over the past, present and future
Searching over the past, present and futureSearching over the past, present and future
Searching over the past, present and future
 
Ecology Essay.pdf
Ecology Essay.pdfEcology Essay.pdf
Ecology Essay.pdf
 
Davos version aug_2014
Davos version aug_2014Davos version aug_2014
Davos version aug_2014
 
AHRC CDP Digital Humanities 101
AHRC CDP Digital Humanities 101  AHRC CDP Digital Humanities 101
AHRC CDP Digital Humanities 101
 
Participant Observation Lecture
Participant Observation LectureParticipant Observation Lecture
Participant Observation Lecture
 
Big Data in the Arts and Humanities: Stirling presentation
Big Data in the Arts and Humanities: Stirling presentationBig Data in the Arts and Humanities: Stirling presentation
Big Data in the Arts and Humanities: Stirling presentation
 

More from Nattiya Kanhabua

Search, Exploration and Analytics of Evolving Data
Search, Exploration and Analytics of Evolving DataSearch, Exploration and Analytics of Evolving Data
Search, Exploration and Analytics of Evolving DataNattiya Kanhabua
 
Towards Concise Preservation by Managed Forgetting: Research Issues and Case ...
Towards Concise Preservation by Managed Forgetting: Research Issues and Case ...Towards Concise Preservation by Managed Forgetting: Research Issues and Case ...
Towards Concise Preservation by Managed Forgetting: Research Issues and Case ...Nattiya Kanhabua
 
Understanding the Diversity of Tweets in the Time of Outbreaks
Understanding the Diversity of Tweets in the Time of OutbreaksUnderstanding the Diversity of Tweets in the Time of Outbreaks
Understanding the Diversity of Tweets in the Time of OutbreaksNattiya Kanhabua
 
Why Is It Difficult to Detect Outbreaks in Twitter?
Why Is It Difficult to Detect Outbreaks in Twitter?Why Is It Difficult to Detect Outbreaks in Twitter?
Why Is It Difficult to Detect Outbreaks in Twitter?Nattiya Kanhabua
 
Leveraging Dynamic Query Subtopics for Time-aware Search Result Diversification
Leveraging Dynamic Query Subtopics for Time-aware Search Result DiversificationLeveraging Dynamic Query Subtopics for Time-aware Search Result Diversification
Leveraging Dynamic Query Subtopics for Time-aware Search Result DiversificationNattiya Kanhabua
 
On the Value of Temporal Anchor Texts in Wikipedia
On the Value of Temporal Anchor Texts in WikipediaOn the Value of Temporal Anchor Texts in Wikipedia
On the Value of Temporal Anchor Texts in WikipediaNattiya Kanhabua
 
Ranking Related News Predictions
Ranking Related News PredictionsRanking Related News Predictions
Ranking Related News PredictionsNattiya Kanhabua
 
Temporal summarization of event related updates
Temporal summarization of event related updatesTemporal summarization of event related updates
Temporal summarization of event related updatesNattiya Kanhabua
 
Temporal Web Dynamics: Implications from Search Perspective
Temporal Web Dynamics: Implications from Search PerspectiveTemporal Web Dynamics: Implications from Search Perspective
Temporal Web Dynamics: Implications from Search PerspectiveNattiya Kanhabua
 
Temporal Web Dynamics and Implications for Information Retrieval
Temporal Web Dynamics and Implications for Information RetrievalTemporal Web Dynamics and Implications for Information Retrieval
Temporal Web Dynamics and Implications for Information RetrievalNattiya Kanhabua
 
Preservation and Forgetting: Friends or Foes?
Preservation and Forgetting: Friends or Foes?Preservation and Forgetting: Friends or Foes?
Preservation and Forgetting: Friends or Foes?Nattiya Kanhabua
 
Concise Preservation by Combining Managed Forgetting and Contextualized Remem...
Concise Preservation by Combining Managed Forgetting and Contextualized Remem...Concise Preservation by Combining Managed Forgetting and Contextualized Remem...
Concise Preservation by Combining Managed Forgetting and Contextualized Remem...Nattiya Kanhabua
 
Can Twitter & Co. Save Lives?
Can Twitter & Co. Save Lives?Can Twitter & Co. Save Lives?
Can Twitter & Co. Save Lives?Nattiya Kanhabua
 
Searching the Temporal Web: Challenges and Current Approaches
Searching the Temporal Web: Challenges and Current ApproachesSearching the Temporal Web: Challenges and Current Approaches
Searching the Temporal Web: Challenges and Current ApproachesNattiya Kanhabua
 
Improving Temporal Language Models For Determining Time of Non-Timestamped Do...
Improving Temporal Language Models For Determining Time of Non-Timestamped Do...Improving Temporal Language Models For Determining Time of Non-Timestamped Do...
Improving Temporal Language Models For Determining Time of Non-Timestamped Do...Nattiya Kanhabua
 
Exploiting temporal information in retrieval of archived documents (doctoral ...
Exploiting temporal information in retrieval of archived documents (doctoral ...Exploiting temporal information in retrieval of archived documents (doctoral ...
Exploiting temporal information in retrieval of archived documents (doctoral ...Nattiya Kanhabua
 
Determining Time of Queries for Re-ranking Search Results
Determining Time of Queries for Re-ranking Search ResultsDetermining Time of Queries for Re-ranking Search Results
Determining Time of Queries for Re-ranking Search ResultsNattiya Kanhabua
 
Supporting Exploration and Serendipity in Information Retrieval
Supporting Exploration and Serendipity in Information RetrievalSupporting Exploration and Serendipity in Information Retrieval
Supporting Exploration and Serendipity in Information RetrievalNattiya Kanhabua
 
Time-aware Approaches to Information Retrieval
Time-aware Approaches to Information RetrievalTime-aware Approaches to Information Retrieval
Time-aware Approaches to Information RetrievalNattiya Kanhabua
 
Learning to Rank Search Results for Time-Sensitive Queries (poster presentation)
Learning to Rank Search Results for Time-Sensitive Queries (poster presentation)Learning to Rank Search Results for Time-Sensitive Queries (poster presentation)
Learning to Rank Search Results for Time-Sensitive Queries (poster presentation)Nattiya Kanhabua
 

More from Nattiya Kanhabua (20)

Search, Exploration and Analytics of Evolving Data
Search, Exploration and Analytics of Evolving DataSearch, Exploration and Analytics of Evolving Data
Search, Exploration and Analytics of Evolving Data
 
Towards Concise Preservation by Managed Forgetting: Research Issues and Case ...
Towards Concise Preservation by Managed Forgetting: Research Issues and Case ...Towards Concise Preservation by Managed Forgetting: Research Issues and Case ...
Towards Concise Preservation by Managed Forgetting: Research Issues and Case ...
 
Understanding the Diversity of Tweets in the Time of Outbreaks
Understanding the Diversity of Tweets in the Time of OutbreaksUnderstanding the Diversity of Tweets in the Time of Outbreaks
Understanding the Diversity of Tweets in the Time of Outbreaks
 
Why Is It Difficult to Detect Outbreaks in Twitter?
Why Is It Difficult to Detect Outbreaks in Twitter?Why Is It Difficult to Detect Outbreaks in Twitter?
Why Is It Difficult to Detect Outbreaks in Twitter?
 
Leveraging Dynamic Query Subtopics for Time-aware Search Result Diversification
Leveraging Dynamic Query Subtopics for Time-aware Search Result DiversificationLeveraging Dynamic Query Subtopics for Time-aware Search Result Diversification
Leveraging Dynamic Query Subtopics for Time-aware Search Result Diversification
 
On the Value of Temporal Anchor Texts in Wikipedia
On the Value of Temporal Anchor Texts in WikipediaOn the Value of Temporal Anchor Texts in Wikipedia
On the Value of Temporal Anchor Texts in Wikipedia
 
Ranking Related News Predictions
Ranking Related News PredictionsRanking Related News Predictions
Ranking Related News Predictions
 
Temporal summarization of event related updates
Temporal summarization of event related updatesTemporal summarization of event related updates
Temporal summarization of event related updates
 
Temporal Web Dynamics: Implications from Search Perspective
Temporal Web Dynamics: Implications from Search PerspectiveTemporal Web Dynamics: Implications from Search Perspective
Temporal Web Dynamics: Implications from Search Perspective
 
Temporal Web Dynamics and Implications for Information Retrieval
Temporal Web Dynamics and Implications for Information RetrievalTemporal Web Dynamics and Implications for Information Retrieval
Temporal Web Dynamics and Implications for Information Retrieval
 
Preservation and Forgetting: Friends or Foes?
Preservation and Forgetting: Friends or Foes?Preservation and Forgetting: Friends or Foes?
Preservation and Forgetting: Friends or Foes?
 
Concise Preservation by Combining Managed Forgetting and Contextualized Remem...
Concise Preservation by Combining Managed Forgetting and Contextualized Remem...Concise Preservation by Combining Managed Forgetting and Contextualized Remem...
Concise Preservation by Combining Managed Forgetting and Contextualized Remem...
 
Can Twitter & Co. Save Lives?
Can Twitter & Co. Save Lives?Can Twitter & Co. Save Lives?
Can Twitter & Co. Save Lives?
 
Searching the Temporal Web: Challenges and Current Approaches
Searching the Temporal Web: Challenges and Current ApproachesSearching the Temporal Web: Challenges and Current Approaches
Searching the Temporal Web: Challenges and Current Approaches
 
Improving Temporal Language Models For Determining Time of Non-Timestamped Do...
Improving Temporal Language Models For Determining Time of Non-Timestamped Do...Improving Temporal Language Models For Determining Time of Non-Timestamped Do...
Improving Temporal Language Models For Determining Time of Non-Timestamped Do...
 
Exploiting temporal information in retrieval of archived documents (doctoral ...
Exploiting temporal information in retrieval of archived documents (doctoral ...Exploiting temporal information in retrieval of archived documents (doctoral ...
Exploiting temporal information in retrieval of archived documents (doctoral ...
 
Determining Time of Queries for Re-ranking Search Results
Determining Time of Queries for Re-ranking Search ResultsDetermining Time of Queries for Re-ranking Search Results
Determining Time of Queries for Re-ranking Search Results
 
Supporting Exploration and Serendipity in Information Retrieval
Supporting Exploration and Serendipity in Information RetrievalSupporting Exploration and Serendipity in Information Retrieval
Supporting Exploration and Serendipity in Information Retrieval
 
Time-aware Approaches to Information Retrieval
Time-aware Approaches to Information RetrievalTime-aware Approaches to Information Retrieval
Time-aware Approaches to Information Retrieval
 
Learning to Rank Search Results for Time-Sensitive Queries (poster presentation)
Learning to Rank Search Results for Time-Sensitive Queries (poster presentation)Learning to Rank Search Results for Time-Sensitive Queries (poster presentation)
Learning to Rank Search Results for Time-Sensitive Queries (poster presentation)
 

Recently uploaded

Andrés Ramírez Gossler, Facundo Schinnea - eCommerce Day Chile 2024
Andrés Ramírez Gossler, Facundo Schinnea - eCommerce Day Chile 2024Andrés Ramírez Gossler, Facundo Schinnea - eCommerce Day Chile 2024
Andrés Ramírez Gossler, Facundo Schinnea - eCommerce Day Chile 2024eCommerce Institute
 
CTAC 2024 Valencia - Sven Zoelle - Most Crucial Invest to Digitalisation_slid...
CTAC 2024 Valencia - Sven Zoelle - Most Crucial Invest to Digitalisation_slid...CTAC 2024 Valencia - Sven Zoelle - Most Crucial Invest to Digitalisation_slid...
CTAC 2024 Valencia - Sven Zoelle - Most Crucial Invest to Digitalisation_slid...henrik385807
 
Exploring protein-protein interactions by Weak Affinity Chromatography (WAC) ...
Exploring protein-protein interactions by Weak Affinity Chromatography (WAC) ...Exploring protein-protein interactions by Weak Affinity Chromatography (WAC) ...
Exploring protein-protein interactions by Weak Affinity Chromatography (WAC) ...Salam Al-Karadaghi
 
Microsoft Copilot AI for Everyone - created by AI
Microsoft Copilot AI for Everyone - created by AIMicrosoft Copilot AI for Everyone - created by AI
Microsoft Copilot AI for Everyone - created by AITatiana Gurgel
 
Motivation and Theory Maslow and Murray pdf
Motivation and Theory Maslow and Murray pdfMotivation and Theory Maslow and Murray pdf
Motivation and Theory Maslow and Murray pdfakankshagupta7348026
 
George Lever - eCommerce Day Chile 2024
George Lever -  eCommerce Day Chile 2024George Lever -  eCommerce Day Chile 2024
George Lever - eCommerce Day Chile 2024eCommerce Institute
 
SaaStr Workshop Wednesday w: Jason Lemkin, SaaStr
SaaStr Workshop Wednesday w: Jason Lemkin, SaaStrSaaStr Workshop Wednesday w: Jason Lemkin, SaaStr
SaaStr Workshop Wednesday w: Jason Lemkin, SaaStrsaastr
 
VVIP Call Girls Nalasopara : 9892124323, Call Girls in Nalasopara Services
VVIP Call Girls Nalasopara : 9892124323, Call Girls in Nalasopara ServicesVVIP Call Girls Nalasopara : 9892124323, Call Girls in Nalasopara Services
VVIP Call Girls Nalasopara : 9892124323, Call Girls in Nalasopara ServicesPooja Nehwal
 
Navi Mumbai Call Girls Service Pooja 9892124323 Real Russian Girls Looking Mo...
Navi Mumbai Call Girls Service Pooja 9892124323 Real Russian Girls Looking Mo...Navi Mumbai Call Girls Service Pooja 9892124323 Real Russian Girls Looking Mo...
Navi Mumbai Call Girls Service Pooja 9892124323 Real Russian Girls Looking Mo...Pooja Nehwal
 
WhatsApp 📞 9892124323 ✅Call Girls In Juhu ( Mumbai )
WhatsApp 📞 9892124323 ✅Call Girls In Juhu ( Mumbai )WhatsApp 📞 9892124323 ✅Call Girls In Juhu ( Mumbai )
WhatsApp 📞 9892124323 ✅Call Girls In Juhu ( Mumbai )Pooja Nehwal
 
OSCamp Kubernetes 2024 | SRE Challenges in Monolith to Microservices Shift at...
OSCamp Kubernetes 2024 | SRE Challenges in Monolith to Microservices Shift at...OSCamp Kubernetes 2024 | SRE Challenges in Monolith to Microservices Shift at...
OSCamp Kubernetes 2024 | SRE Challenges in Monolith to Microservices Shift at...NETWAYS
 
Russian Call Girls in Kolkata Vaishnavi 🤌 8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Vaishnavi 🤌  8250192130 🚀 Vip Call Girls KolkataRussian Call Girls in Kolkata Vaishnavi 🤌  8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Vaishnavi 🤌 8250192130 🚀 Vip Call Girls Kolkataanamikaraghav4
 
Re-membering the Bard: Revisiting The Compleat Wrks of Wllm Shkspr (Abridged)...
Re-membering the Bard: Revisiting The Compleat Wrks of Wllm Shkspr (Abridged)...Re-membering the Bard: Revisiting The Compleat Wrks of Wllm Shkspr (Abridged)...
Re-membering the Bard: Revisiting The Compleat Wrks of Wllm Shkspr (Abridged)...Hasting Chen
 
Night 7k Call Girls Noida Sector 128 Call Me: 8448380779
Night 7k Call Girls Noida Sector 128 Call Me: 8448380779Night 7k Call Girls Noida Sector 128 Call Me: 8448380779
Night 7k Call Girls Noida Sector 128 Call Me: 8448380779Delhi Call girls
 
OSCamp Kubernetes 2024 | A Tester's Guide to CI_CD as an Automated Quality Co...
OSCamp Kubernetes 2024 | A Tester's Guide to CI_CD as an Automated Quality Co...OSCamp Kubernetes 2024 | A Tester's Guide to CI_CD as an Automated Quality Co...
OSCamp Kubernetes 2024 | A Tester's Guide to CI_CD as an Automated Quality Co...NETWAYS
 
call girls in delhi malviya nagar @9811711561@
call girls in delhi malviya nagar @9811711561@call girls in delhi malviya nagar @9811711561@
call girls in delhi malviya nagar @9811711561@vikas rana
 
Philippine History cavite Mutiny Report.ppt
Philippine History cavite Mutiny Report.pptPhilippine History cavite Mutiny Report.ppt
Philippine History cavite Mutiny Report.pptssuser319dad
 
Call Girls in Sarojini Nagar Market Delhi 💯 Call Us 🔝8264348440🔝
Call Girls in Sarojini Nagar Market Delhi 💯 Call Us 🔝8264348440🔝Call Girls in Sarojini Nagar Market Delhi 💯 Call Us 🔝8264348440🔝
Call Girls in Sarojini Nagar Market Delhi 💯 Call Us 🔝8264348440🔝soniya singh
 
Open Source Camp Kubernetes 2024 | Running WebAssembly on Kubernetes by Alex ...
Open Source Camp Kubernetes 2024 | Running WebAssembly on Kubernetes by Alex ...Open Source Camp Kubernetes 2024 | Running WebAssembly on Kubernetes by Alex ...
Open Source Camp Kubernetes 2024 | Running WebAssembly on Kubernetes by Alex ...NETWAYS
 
OSCamp Kubernetes 2024 | Zero-Touch OS-Infrastruktur für Container und Kubern...
OSCamp Kubernetes 2024 | Zero-Touch OS-Infrastruktur für Container und Kubern...OSCamp Kubernetes 2024 | Zero-Touch OS-Infrastruktur für Container und Kubern...
OSCamp Kubernetes 2024 | Zero-Touch OS-Infrastruktur für Container und Kubern...NETWAYS
 

Recently uploaded (20)

Andrés Ramírez Gossler, Facundo Schinnea - eCommerce Day Chile 2024
Andrés Ramírez Gossler, Facundo Schinnea - eCommerce Day Chile 2024Andrés Ramírez Gossler, Facundo Schinnea - eCommerce Day Chile 2024
Andrés Ramírez Gossler, Facundo Schinnea - eCommerce Day Chile 2024
 
CTAC 2024 Valencia - Sven Zoelle - Most Crucial Invest to Digitalisation_slid...
CTAC 2024 Valencia - Sven Zoelle - Most Crucial Invest to Digitalisation_slid...CTAC 2024 Valencia - Sven Zoelle - Most Crucial Invest to Digitalisation_slid...
CTAC 2024 Valencia - Sven Zoelle - Most Crucial Invest to Digitalisation_slid...
 
Exploring protein-protein interactions by Weak Affinity Chromatography (WAC) ...
Exploring protein-protein interactions by Weak Affinity Chromatography (WAC) ...Exploring protein-protein interactions by Weak Affinity Chromatography (WAC) ...
Exploring protein-protein interactions by Weak Affinity Chromatography (WAC) ...
 
Microsoft Copilot AI for Everyone - created by AI
Microsoft Copilot AI for Everyone - created by AIMicrosoft Copilot AI for Everyone - created by AI
Microsoft Copilot AI for Everyone - created by AI
 
Motivation and Theory Maslow and Murray pdf
Motivation and Theory Maslow and Murray pdfMotivation and Theory Maslow and Murray pdf
Motivation and Theory Maslow and Murray pdf
 
George Lever - eCommerce Day Chile 2024
George Lever -  eCommerce Day Chile 2024George Lever -  eCommerce Day Chile 2024
George Lever - eCommerce Day Chile 2024
 
SaaStr Workshop Wednesday w: Jason Lemkin, SaaStr
SaaStr Workshop Wednesday w: Jason Lemkin, SaaStrSaaStr Workshop Wednesday w: Jason Lemkin, SaaStr
SaaStr Workshop Wednesday w: Jason Lemkin, SaaStr
 
VVIP Call Girls Nalasopara : 9892124323, Call Girls in Nalasopara Services
VVIP Call Girls Nalasopara : 9892124323, Call Girls in Nalasopara ServicesVVIP Call Girls Nalasopara : 9892124323, Call Girls in Nalasopara Services
VVIP Call Girls Nalasopara : 9892124323, Call Girls in Nalasopara Services
 
Navi Mumbai Call Girls Service Pooja 9892124323 Real Russian Girls Looking Mo...
Navi Mumbai Call Girls Service Pooja 9892124323 Real Russian Girls Looking Mo...Navi Mumbai Call Girls Service Pooja 9892124323 Real Russian Girls Looking Mo...
Navi Mumbai Call Girls Service Pooja 9892124323 Real Russian Girls Looking Mo...
 
WhatsApp 📞 9892124323 ✅Call Girls In Juhu ( Mumbai )
WhatsApp 📞 9892124323 ✅Call Girls In Juhu ( Mumbai )WhatsApp 📞 9892124323 ✅Call Girls In Juhu ( Mumbai )
WhatsApp 📞 9892124323 ✅Call Girls In Juhu ( Mumbai )
 
OSCamp Kubernetes 2024 | SRE Challenges in Monolith to Microservices Shift at...
OSCamp Kubernetes 2024 | SRE Challenges in Monolith to Microservices Shift at...OSCamp Kubernetes 2024 | SRE Challenges in Monolith to Microservices Shift at...
OSCamp Kubernetes 2024 | SRE Challenges in Monolith to Microservices Shift at...
 
Russian Call Girls in Kolkata Vaishnavi 🤌 8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Vaishnavi 🤌  8250192130 🚀 Vip Call Girls KolkataRussian Call Girls in Kolkata Vaishnavi 🤌  8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Vaishnavi 🤌 8250192130 🚀 Vip Call Girls Kolkata
 
Re-membering the Bard: Revisiting The Compleat Wrks of Wllm Shkspr (Abridged)...
Re-membering the Bard: Revisiting The Compleat Wrks of Wllm Shkspr (Abridged)...Re-membering the Bard: Revisiting The Compleat Wrks of Wllm Shkspr (Abridged)...
Re-membering the Bard: Revisiting The Compleat Wrks of Wllm Shkspr (Abridged)...
 
Night 7k Call Girls Noida Sector 128 Call Me: 8448380779
Night 7k Call Girls Noida Sector 128 Call Me: 8448380779Night 7k Call Girls Noida Sector 128 Call Me: 8448380779
Night 7k Call Girls Noida Sector 128 Call Me: 8448380779
 
OSCamp Kubernetes 2024 | A Tester's Guide to CI_CD as an Automated Quality Co...
OSCamp Kubernetes 2024 | A Tester's Guide to CI_CD as an Automated Quality Co...OSCamp Kubernetes 2024 | A Tester's Guide to CI_CD as an Automated Quality Co...
OSCamp Kubernetes 2024 | A Tester's Guide to CI_CD as an Automated Quality Co...
 
call girls in delhi malviya nagar @9811711561@
call girls in delhi malviya nagar @9811711561@call girls in delhi malviya nagar @9811711561@
call girls in delhi malviya nagar @9811711561@
 
Philippine History cavite Mutiny Report.ppt
Philippine History cavite Mutiny Report.pptPhilippine History cavite Mutiny Report.ppt
Philippine History cavite Mutiny Report.ppt
 
Call Girls in Sarojini Nagar Market Delhi 💯 Call Us 🔝8264348440🔝
Call Girls in Sarojini Nagar Market Delhi 💯 Call Us 🔝8264348440🔝Call Girls in Sarojini Nagar Market Delhi 💯 Call Us 🔝8264348440🔝
Call Girls in Sarojini Nagar Market Delhi 💯 Call Us 🔝8264348440🔝
 
Open Source Camp Kubernetes 2024 | Running WebAssembly on Kubernetes by Alex ...
Open Source Camp Kubernetes 2024 | Running WebAssembly on Kubernetes by Alex ...Open Source Camp Kubernetes 2024 | Running WebAssembly on Kubernetes by Alex ...
Open Source Camp Kubernetes 2024 | Running WebAssembly on Kubernetes by Alex ...
 
OSCamp Kubernetes 2024 | Zero-Touch OS-Infrastruktur für Container und Kubern...
OSCamp Kubernetes 2024 | Zero-Touch OS-Infrastruktur für Container und Kubern...OSCamp Kubernetes 2024 | Zero-Touch OS-Infrastruktur für Container und Kubern...
OSCamp Kubernetes 2024 | Zero-Touch OS-Infrastruktur für Container und Kubern...
 

Combining Managed Forgetting and Contextualized Remembering

  • 1. “Concise Preservation by Combining Managed Forgetting and Contextualized Remembering” EU/FP7 ForgetIT Project (2013-2016) http://www.forgetit-project.eu What Triggers Human Remembering of Events? Large-Scale Analysis of Collective Memory in Wikipedia Nattiya Kanhabua, Tu Ngoc Nguyen and Claudia Niederée L3S Research Center , Hannover, Germany
  • 2. Motivation: ForgetIT Project Human Forgetting and Remembering Collective Memory in Wikipedia Experiments and Discussion Conclusions Outline
  • 3. However, we are facing: • Dramatic increase in content creation (e.g. digital photos) • Increasing use of mobile devices with restricted capacity • Information overload and changing professional and private lives • Inadvertent forgetting due to lack of systematic preservation Forgetting plays a crucial role for human remembering and life (focus on current, relevant information; ignore redundant details) Managed forgetting ≠ automatic deletion Instead: a range of forgetting options e.g. • Resource condensation • Change of indexing & ranking • Reduction of redundancy A computer that forgets intentionally ? And, in context of digital preservation??
  • 4. However, we are facing: • Dramatic increase in content creation (e.g. digital photos) • Increasing use of mobile devices with restricted capacity • Information overload and changing professional and private lives • Inadvertent forgetting due to lack of systematic preservation Forgetting plays a crucial role for human remembering and life (focus on current, relevant information; ignore redundant details) Managed forgetting ≠ automatic deletion Instead: a range of forgetting options e.g. • Resource condensation • Change of indexing & ranking • Reduction of redundancy A computer that forgets intentionally ? And, in context of digital preservation?? Managed forgetting = to remember the right information
  • 5. Individual memories are subject to a fast forgetting process [Ebbinghaus, 1885] • Rapidly forget details -> “less redundancy” Episodic memory (of one’s past event) is reconstructed from similar events/context • Rely on common patterns -> “false memory” Memory bumps in the forgetting curve is caused by reminding or triggering of: • A physical object (e.g. a printed photo) • A digital memory system • Different subsequent events Human Forgetting and Remembering H. Ebbinghaus, Über das Gedächtnis. Untersuchungen zur experimentellen Psychologie. Duncker & Humblot, Leipzig, 1885. E. Tulving, Episodic memory: From mind to brain. Annual review of psychology, vol. 53, no. 1, pp. 1-25, 2002.
  • 6. “ Collective memory is a socially constructed, common image (memory) of the past of a community, which frames its current understanding and actions.” [Halbwachs, 1950] • Crowd phenomenon and important to societal processes • Not static as determined by the concerns of the present From Individual Memories to Collective Memory M. Halbwachs, On collective memory. Chicago: The University of Chicago Press, 1950 (Translation). Flashbulb memories in cognitive psychology • A study of remembering of high-impact events, e.g., The British Royal Wedding or September 11 attacks • Aspects: details, confidence, consistency of memory over time, impact of media coverage • Qualitative study: limited number of events and users
  • 7. Collective Memory in Wikipedia Wikipedia as a source for global memory • Largest and most up-to-date online encyclopedia (19M registered users, 30K active editors) • Social negotiation and construction reflected in early editing activities and talk pages • Indicators for identifying real-world events C. Pentzold, The online encyclopaedia wikipedia as a global memory place, Memory Studies, 2009. M. Georgescu, N. Kanhabua, D. Krause, W. Nejdl, and S. Siersdorfer, Extracting event-related information from article updates in wikipedia, ECIR'2013. View logs as the signal for collective memory • Public page view traffics with a long time span • Not directly reflect how people forget; significant patterns are a good estimate public remembering • Large-scale analysis complements (1) qualitative studies (2) analyzing article content (scalability)
  • 8. Contributions First study of identifying catalysts for event memory triggering by using time series analysis techniques: • temporal correlations in peaking page visits between events, • a surprise score or the residual sum of squares on prediction error, and • the skewness of view shapes as a catalyst for memories Identify the relationship between events by using different features • the role of time passed, the same types of events, the size or magnitude of events, the near-by city or neighbor country Analyze over 5500 high-impact events from 11 event categories Related to the previous study by [Au Yeung and Jatowt, 2011] • Analyzed references to the past (as an indicator to what is remembered) in a large news collection for identifying, which years are most frequently referenced C.-m. Au Yeung and A. Jatowt, Studying how the past is remembered: Towards computational history through large scale text mining, CIKM’2011
  • 9. We propose a 3-step approach, for a given event: 1. Compute “remembering scores” of past events within the same category 2. Rank related past events by the computed remembering scores 3. Identify features (e.g., time, location) having a high correlation with remembering Our Approach
  • 10. Remembering scores: a linear combination of three features: 1. Cross-correlation coefficient (CCF) 2. Sum of squared error (SSE) 3. Skewness (Kurtosis) Measuring Signals for Memory Revival
  • 11. Remembering scores: a linear combination of three features: 1. Cross-correlation coefficient (CCF) 2. Sum of squared error (SSE) 3. Skewness (Kurtosis) Measuring Signals for Memory Revival
  • 12. Remembering scores: a linear combination of three features: 1. Cross-correlation coefficient (CCF) 2. Sum of squared error (SSE) 3. Skewness (Kurtosis) Measuring Signals for Memory Revival Remembering = α•CCF + β•SSE + γ•Kurtosis
  • 13. Features for Triggered Remembering Temporal similarity: • Time distance between two events (in days, months or years) • Time distance based on exponential decay functions Location similarity: • Map a geographic hierarchy of event locations as follows  city -> state -> country -> neighbor countries -> continent • Assign 4 scale values: 4 to same city, 3 to state, 2 to country,1 to continent Impact of Events: • Damaged area/properties/cost/fatalities • Magnitude (for earthquake events) • Highest winds, lowest pressure (for Atlantic hurricanes) N. Kanhabua and K. Nørvåg: Determining time of queries for re-ranking search results. ECDL 2010 J. Strötgen, M. Gertz, and C. Junghans: An event-centric model for multilingual document similarity. SIGIR 2011
  • 14. Experiments Datasets: • Page views statistics 2007-2013 • A large set of 5,500 events • From 11 event-related categories • α = 0.5, β = 0.4, γ = 0.1
  • 15. Temporal and spatial distributions • Strong focus on more recent events • Better coverage with increasing popularity • Most frequent locations depending on event types Temporal and Spatial Distributions
  • 16. Temporal and spatial distributions • Strong focus on more recent events • Better coverage with increasing popularity • Most frequent locations depending on event types Temporal and Spatial Distributions
  • 17. Temporal and spatial distributions • Strong focus on more recent events • Better coverage with increasing popularity • Most frequent locations depending on event types Temporal and Spatial Distributions
  • 18. Category: Atlantic Hurricane Distributions of remembering scores • Hurricane Sandy (Form date: October 22, 2012, Affected area: Mid-Atlantic) • Hurricane Hanna (Form date: August 28, 2008, Affected area: US east coast)
  • 19. Category: Atlantic Hurricane Distributions of remembering scores • Hurricane Sandy (Form date: October 22, 2012, Affected area: Mid-Atlantic) • Hurricane Hanna (Form date: August 28, 2008, Affected area: US east coast) Location and time have a low effect on remembering scores for this category.
  • 20. Category: Atlantic Hurricane Top-10 events triggered by the two events • Hurricane Hanna commemorates Hurricane Gustav, the freshest hurricane stuck at the area of Puerto Rico and East Coast • Hurricane Sandy triggers 1991 Perfect Storm initially formed around Canada area, which t is high impact and most destructive
  • 21. Category: Atlantic Hurricane Top-10 events triggered by the two events • Hurricane Hanna commemorates Hurricane Gustav, the freshest hurricane stuck at the area of Puerto Rico and East Coast • Hurricane Sandy triggers 1991 Perfect Storm initially formed around Canada area, which t is high impact and most destructive
  • 22. Category: Aviation accidents Mixture of impact factors, such as, time and location • Qantas Flight 32 (crashed on 4 November 2010) triggers remembering of (1) Qantas Flight 30 and British Airways Flight 9 (both going to Australia), and (2) Aero Caribbean Flight 883 (most recent event) Most recent
  • 23. Category: Aviation accidents Mixture of impact factors, such as, time and location • Qantas Flight 32 (crashed on 4 November 2010) triggers remembering of (1) Qantas Flight 30 and British Airways Flight 9 (both going to Australia), and (2) Aero Caribbean Flight 883 (most recent event) Same destination
  • 24. Category: Aviation accidents Mixture of impact factors, such as, time and location • Qantas Flight 32 (crashed on 4 November 2010) triggers remembering of (1) Qantas Flight 30 and British Airways Flight 9 (both going to Australia), and (2) Aero Caribbean Flight 883 (most recent event) Same destination Deadliest (two aircraft collided) Concorde
  • 25. Category: Earthquakes A series of earthquake events at Christchurch, New Zealand • 2010 Canterbury earthquake triggers 2010 Haiti earthquake (recent and high- impact) and two close-by events, and high-impact historical earthquakes • 2011 Christchurch earthquake shows locality focus, i.e., people seem to be interested in the previous events in the same region • June 2011 Christchurch earthquake, the remembered events are dominated by the two predecessor events
  • 26. Category: Earthquakes A series of earthquake events at Christchurch, New Zealand • 2010 Canterbury earthquake triggers 2010 Haiti earthquake (recent and high- impact) and two close-by events, and high-impact historical earthquakes • 2011 Christchurch earthquake shows locality focus, i.e., people seem to be interested in the previous events in the same region • June 2011 Christchurch earthquake, the remembered events are dominated by the two predecessor events
  • 27. Category: Earthquakes A series of earthquake events at Christchurch, New Zealand • 2010 Canterbury earthquake triggers 2010 Haiti earthquake (recent and high- impact) and two close-by events, and high-impact historical earthquakes • 2011 Christchurch earthquake shows locality focus, i.e., people seem to be interested in the previous events in the same region • June 2011 Christchurch earthquake, the remembered events are dominated by the two predecessor events
  • 28. Category: Earthquakes A series of earthquake events at Christchurch, New Zealand • 2010 Canterbury earthquake triggers 2010 Haiti earthquake (recent and high- impact) and two close-by events, and high-impact historical earthquakes • 2011 Christchurch earthquake shows locality focus, i.e., people seem to be interested in the previous events in the same region • June 2011 Christchurch earthquake, the remembered events are dominated by the two predecessor events Look beyond single events, especially, if there are several events in temporal and local proximity.
  • 29. Category: Earthquakes A series of earthquake events at Christchurch, New Zealand • 2010 Canterbury earthquake triggers 2010 Haiti earthquake (recent and high- impact) and two close-by events, and high-impact historical earthquakes • 2011 Christchurch earthquake shows locality focus, i.e., people seem to be interested in the previous events in the same region • June 2011 Christchurch earthquake, the remembered events are dominated by the two predecessor events Look beyond single events, especially, if there are several events in temporal and local proximity.
  • 30. Category: Terrorist incidents Interesting observation: semantic similarity between events • June 2012 Kaduna church bombings triggers other religion terror attacks • 2008 Mumbai attacks trigger terror attacks in business, entertainment and hotels 2nd 5th 24th
  • 31. Category: Terrorist incidents Interesting observation: semantic similarity between events • June 2012 Kaduna church bombings triggers other religion terror attacks • 2008 Mumbai attacks trigger terror attacks in business, entertainment and hotels 2nd 7th 15th
  • 32. Conclusions We identified some first pattern for event memory triggering for diverse event types including natural and manmade disasters as well as accidents and terrorism. Our analysis confirmed the influence of closeness in time and location, but the semantic similarity of events also influences which event memories are triggered by an event. In our future work, we plan to deepen our systematic analysis of factors for revisiting past events and of the combination of those factors. We also plan to investigate external factors such as media coverage linking new events to past events or reflection of such relationships in other types of social media.
  • 33. What do you remember? Thanks for your attention!