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Dear Kamal, Thanks for sharing your abstract. Please forward a preprint for me to read.

 

Alessandro, your work seems interesting as well.

 

I find both papers very relevant to some work I am doing in the area. We very recently presented our paper “Social Influence Computation and Maximization in Signed Networks with Competing Cascades” at ASONAM 2015. If interested, I can forward a preprint of that work as well.

 

Sincerely,

Charalampos Chelmis

Senior Research Associate

Ming Hsieh Department of Electrical Engineering

Viterbi School of Engineering

University of Southern California

 

From: Social Networks Discussion Forum [mailto:[log in to unmask]] On Behalf Of Amit Rechavi
Sent: Thursday, September 24, 2015 12:14
To: [log in to unmask]
Subject: Re: [SOCNET] Negative ties, ambivalence and positive/negative gossip

 

***** To join INSNA, visit http://www.insna.org *****

Negative Link Prediction in Social Media
Jiliang Tang, Shiyu Chang, Charu Aggarwal and Huan Liu
WSDM’15, February 2–6, 2015, Shanghai, China.


Amit Rechavi, Ph.D

Network Research

  
http://amitre.wix.com/amitrechavi

 

 

 

2015-09-24 22:01 GMT+03:00 Alessandro Bessi <[log in to unmask]>:

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Dear Kamal,


in our recent paper "Echo chambers in the age of misinformation", we derive a data-driven percolation model on signed networks to explain information diffusion of conflicting narratives (and rumors spreading) on online social networks. Maybe you can find it useful.

arXiv: http://arxiv.org/abs/1509.00189

Best,

 

On Thu, Sep 24, 2015 at 8:18 PM, Olivier Walther <[log in to unmask]> wrote:

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Dear Kamal,

 

David Skillicorn, Quan Zheng and I will present a paper in which spectral embedding techniques for directed graphs and signed graphs can be combined to the ISI-ICDM conference in Atlantic City in November. If you are interested, I'll send you a copy. The abstract can be found below.

 

"Signed Directed Social Network Analysis Applied to Group Conflict". Abstract—Real-world social networks contain relationships of multiple different types, but this richness is often ignored in graph-theoretic modelling. We show how two recently developed spectral embedding techniques, for directed graphs (relationships are asymmetric) and for signed graphs (relationships are both positive and negative), can be combined. This combination is particularly appropriate for intelligence, terrorism, and law enforcement applications. We illustrate by applying the novel embedding technique to datasets describing conflict in North-West Africa, and show how unusual interactions can be identified.

 

Kind regards,

 

Olivier

 

 

--
Olivier J. Walther, Ph.D.
Associate Professor

Department of Border Region Studies
University of Southern Denmark
DK-6400 Sønderborg
+45.65.50.83.93
Twitter: @ojwalther


From: Social Networks Discussion Forum [[log in to unmask]] on behalf of Michael Szell [[log in to unmask]]
Sent: Thursday, September 24, 2015 6:43 PM
To: [log in to unmask]
Subject: Re: [SOCNET] Negative ties, ambivalence and positive/negative gossip

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Hi Kamal,

maybe one of the main reasons for the lopsided focus on positive rather than negative ties is the difficulties in acquiring negative tie data. That said, there are increasing efforts in mapping out this so far mostly "hidden", but potentially much more important negative part of social systems.

Besides the important works by Labianca et al that you mentioned, some recent nice papers on the topic can be found here: http://recens.tk.mta.hu/en/publications-and-research-papers

Some works of mine also focused on signed networks in an online environment following a multiplex network approach: http://www.pnas.org/content/107/31/13636 http://www.sciencedirect.com/science/article/pii/S0378873310000316

And there are some papers from the computer science community focusing on large-scale data sets, for example: http://dl.acm.org/citation.cfm?id=1753532 http://dl.acm.org/citation.cfm?id=1772756 

 

None of them, as far as I am aware, has linked this explicitly to the topic of gossip, but that is an interesting next step. The bottleneck is always the data though. One possibility could be to look into publicly available data such as the Enron corpus or communication on Twitter. These have been studied extensively in the context of sentiment analysis, but, as far as I know, not in both the contexts of signed networks and gossip.

Best,

Michael


Postdoctoral Research Associate

 

 

On Thu, Sep 24, 2015 at 12:09 PM, Kamal Badar <[log in to unmask]> wrote:

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Dear All,

 

Literature on work place gossip talks about network ties and their relation to positive/negative work place gossip (e.g. Ellwardt, Steglich & Wittek, 2012; Ellwardt, Labianca & Witteka, 2012 ; Grosser, Lopez-Kidwell & Labianca, 2010). Mostly studies consider the association of multiplex network ties of positive valance (e.g. friendship-instrumental ties) with positive/negative gossip or ties solely of positive valance and their association with positive/negative gossip. 

 

The literature is surprisingly silent when it comes to negative ties (e.g. dislike) and ambivalent multiplex ties (e.g. friendship-hindrance) and their relation to positive/negative gossip. Even recommendations for future research in many research studies is silent.  

 

What might be the reason? Or is there actually some research available? Is is REALLY an avenue to explore or am I thinking in the wrong direction?

 

Regards              

 

--

 

Dr. Kamal Badar

Assistant Professor (TTS)

HEC Approved Ph.D. Supervisor

Institute of Management Sciences
University of Balochistan

Quetta, Pakistan. 

 

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--

Alessandro Bessi

Mobile: +39.3313427237

Twitter: @ibbessi

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