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Professor Amr Ahmed
Professor Amr Ahmed

Professor Amr Ahmed

Active researcher on medical imaging and video analysis

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Tag: Text Analysis

Posted on March 16, 2011

Analyzing Bloggers’ Patterns, from written text only.

 

Analyzing Patterns of Bloggers for Authorship Identification and Group Detection.

Haytham Mohtasseb, Amr Ahmed*, David Cobham

Authorship Identification and Grouping1
Poster – Click to download the PDF version.

INTRODUCTION

Web 2.0 facilitates for individuals to easily generate contents. Blogs and online personal diaries are increasingly popular form of online user-generated contents (UGC).

 

That increasing volume of data need to be analysed and mined to benefit from it.

 

AIM

* Analyse the Patterns of Bloggers, from there written text (in Blogs and Personal diaries)

Analysing this unstructured and free-form text is important and useful in various applications including mood classification, identifying the identify and style of the author, detecting groups, suggesting friends, and targeting specific audiences (e.g. Marketing).

 

Building “User Profile” and “Group Profile”

User Profile: Using text analysis and Psycholinguistic categories to capture the writing style and patterns of each blogger.

Group Profile: Cluster bloggers together, based on their “User Profiles” to form groups of similar bloggers.

 

“Group Profile” Analysis

Automatic Semantic analysis and Psycholinguistic interpretation of commonality within detected groups (only from their written text).

 

Two-Layer Grouping and Authorship Identification

To an identify the author of a (anonymous) blog post, the system utilises the “Group Profiles” and “User Profiles”, respectively. First, the post is assigned to the relevant group (in Group Layer). Then, the post is attributed to a specific Author of that group (in the Author Layer).

 

CONCLUSION

•Automatic analysis of bloggers pattern, using style and psycholinguistic properties, and building “User Profiles”.
•Automatically identify groups and their common properties. This can be used to target audience and/or suggest friends.
•Features set include linguistics and Psycholinguistic features, facilitating for further semantic analysis.

Publications

  1. Two-layered Blogger identification model integrating profile and instance-based methods 
    Mohtasseb Billah, Haytham and Ahmed, Amr (2012) Two-layered Blogger identification model integrating profile and instance-based methods. Knowledge and Information Systems, 31 (1). pp. 1-21. ISSN 0219-1377
  2. PSYCHONET 2: contextualized and enriched psycholinguistic commonsense ontology 
    Mohtasseb Billah, Haytham and Ahmed, Amr and Altadmri, Amjad and Cobham, David (2011) PSYCHONET 2: contextualized and enriched psycholinguistic commonsense ontology. In: KEOD 2011 – International Conference on Knowledge Engineering and Ontology Development, 25 – 29 October 2011, Paris, France.
  3. The affects of demographics differentiations on authorship identification 
    Mohtasseb Billah, Haytham and Ahmed, Amr (2010) The affects of demographics differentiations on authorship identification. Electronic Engineering and Computing Technology; Lecture Notes in Electrical Engineering 2010, 60 . pp. 409-417. ISSN 1876-1100.
  4. PsychoNet: a psycholinguistc commonsense ontology 
    Mohtasseb , Haytham and Ahmed, Amr (2010) PsychoNet: a psycholinguistc commonsense ontology. In: KEOD 2010 International Conference on Knowledge Engineering and Ontology Development part of IC3K, 25 – 28 October, 2010, Valencia, Spain.
  5. More blogging features for author identification 
    Mohtasseb, Haytham and Ahmed, Amr (2009) More blogging features for author identification. In: The 2009 International Conference on Knowledge Discovery (ICKD’09), 2009, Manila.
  6. Mining online diaries for blogger identification 
    Mohtasseb , Haytham and Ahmed, Amr (2009) Mining online diaries for blogger identification. In: The 2009 International Conference of Data Mining and Knowledge Engineering – The World Congress on Engineering, 1 – 3 July, 2009, London, UK.

Vacancies & Opportunities

Short-term RA vacancy:

We have a vacancy for a short-term RA, for up to 6 months. Paid on a rate of up to RM3000 per month, this is suitable for senior PhD researcher who is experienced in Deep Learning and particularly its application in Pathological Image Analysis for detection & classification of Cancer. Candidates are expected to hit the ground running from day 0, given the short period.

Qualified candidates are encouraged to send their CV (highlighting their relevant experience to the above) ASAP, to Dr Amr Ahmed at Amr.Ahmed@nottingham.edu.my

Dr Amr Ahmed

Head of School -Director of the CiH research group

School of Computer Science

University of Nottingham – Malaysia Campus

Jalan Broga, 43500 Semenyih, Selangor Darul Ehsan

Tel: +60 3 8924 8145

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About

Professor Amr Ahmed

& His Research Group

ResearchID:
http://www.researcherid.com/rid/A-4585-2009

Contact

Email: aahmed.unmc@gmail.com

ResearchGate:
https://www.researchgate.net/profile/Amr_Ahmed

ORCID:
https://orcid.org/0000-0002-7749-7911

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